## This file has been created automatically by 'rfGenerateModels'. RMplus <- function(C0, C1, C2, C3, C4, C5, C6, C7, C8, C9, var, scale, Aniso, proj) { cl <- match.call() submodels <- par.general <- par.model <- list() if (hasArg(C0)) submodels[['C0']] <- C0 if (hasArg(C1)) submodels[['C1']] <- C1 if (hasArg(C2)) submodels[['C2']] <- C2 if (hasArg(C3)) submodels[['C3']] <- C3 if (hasArg(C4)) submodels[['C4']] <- C4 if (hasArg(C5)) submodels[['C5']] <- C5 if (hasArg(C6)) submodels[['C6']] <- C6 if (hasArg(C7)) submodels[['C7']] <- C7 if (hasArg(C8)) submodels[['C8']] <- C8 if (hasArg(C9)) submodels[['C9']] <- C9 if (hasArg('var') && !is.null(subst <- substitute(var))) par.general[['var']] <- CheckArg(var, subst, TRUE) if (hasArg('scale') && !is.null(subst <- substitute(scale))) par.general[['scale']] <- CheckArg(scale, subst, TRUE) if (hasArg('Aniso') && !is.null(subst <- substitute(Aniso))) par.general[['Aniso']] <- CheckArg(Aniso, subst, TRUE) if (hasArg('proj') && !is.null(subst <- substitute(proj))) par.general[['proj']] <- CheckMixed(proj, subst, PROJECTION_NAMES) model <- methods::new('RMmodel', call = cl, name = 'RMplus', submodels = submodels, par.model = par.model, par.general = par.general) return(model) } RMplus <- new(CLASS_RM, .Data = RMplus, type = c('of manifold type'), isotropy = c('submodel dependent'), domain = c('submodel dependent'), operator = TRUE, monotone = 'submodel dependent monotonicity', finiterange = NA, simpleArguments = TRUE, maxdim = -3, vdim = -3 ) RMmult <- function(C0, C1, C2, C3, C4, C5, C6, C7, C8, C9, var, scale, Aniso, proj) { cl <- match.call() submodels <- par.general <- par.model <- list() if (hasArg(C0)) submodels[['C0']] <- C0 if (hasArg(C1)) submodels[['C1']] <- C1 if (hasArg(C2)) submodels[['C2']] <- C2 if (hasArg(C3)) submodels[['C3']] <- C3 if (hasArg(C4)) submodels[['C4']] <- C4 if (hasArg(C5)) submodels[['C5']] <- C5 if (hasArg(C6)) submodels[['C6']] <- C6 if (hasArg(C7)) submodels[['C7']] <- C7 if (hasArg(C8)) submodels[['C8']] <- C8 if (hasArg(C9)) submodels[['C9']] <- C9 if (hasArg('var') && !is.null(subst <- substitute(var))) par.general[['var']] <- CheckArg(var, subst, TRUE) if (hasArg('scale') && !is.null(subst <- substitute(scale))) par.general[['scale']] <- CheckArg(scale, subst, TRUE) if (hasArg('Aniso') && !is.null(subst <- substitute(Aniso))) par.general[['Aniso']] <- CheckArg(Aniso, subst, TRUE) if (hasArg('proj') && !is.null(subst <- substitute(proj))) par.general[['proj']] <- CheckMixed(proj, subst, PROJECTION_NAMES) model <- methods::new('RMmodel', call = cl, name = 'RMmult', submodels = submodels, par.model = par.model, par.general = par.general) return(model) } RMmult <- new(CLASS_RM, .Data = RMmult, type = c('of manifold type'), isotropy = c('submodel dependent'), domain = c('submodel dependent'), operator = TRUE, monotone = 'submodel dependent monotonicity', finiterange = NA, simpleArguments = TRUE, maxdim = -3, vdim = -3 ) RMS <- function(phi, var, scale, Aniso, proj, anisoT) { cl <- match.call() submodels <- par.general <- par.model <- list() if (hasArg(phi)) submodels[['phi']] <- phi if (hasArg('var') && !is.null(subst <- substitute(var))) par.model[['var']] <- CheckArg(var, subst, TRUE) if (hasArg('scale') && !is.null(subst <- substitute(scale))) par.model[['scale']] <- CheckArg(scale, subst, TRUE) if (hasArg('anisoT') && !is.null(subst <- substitute(anisoT))) par.model[['anisoT']] <- CheckArg(anisoT, subst, TRUE) if (hasArg('Aniso') && !is.null(subst <- substitute(Aniso))) par.model[['Aniso']] <- CheckArg(Aniso, subst, TRUE) if (hasArg('proj') && !is.null(subst <- substitute(proj))) par.model[['proj']] <- CheckMixed(proj, subst, PROJECTION_NAMES) model <- methods::new('RMmodel', call = cl, name = 'RMS', submodels = submodels, par.model = par.model, par.general = par.general) return(model) } RMS <- new(CLASS_RM, .Data = RMS, type = c('of manifold type', 'of manifold type'), isotropy = c('submodel dependent', 'submodel dependent'), domain = c('submodel dependent'), operator = TRUE, monotone = 'submodel dependent monotonicity', finiterange = NA, simpleArguments = TRUE, maxdim = -3, vdim = -3 ) RMave <- function(phi, A, z, spacetime, var, scale, Aniso, proj) { cl <- match.call() submodels <- par.general <- par.model <- list() if (hasArg(phi)) submodels[['phi']] <- phi if (hasArg('A') && !is.null(subst <- substitute(A))) par.model[['A']] <- CheckArg(A, subst, TRUE) if (hasArg('z') && !is.null(subst <- substitute(z))) par.model[['z']] <- CheckArg(z, subst, TRUE) if (hasArg('spacetime') && !is.null(subst <- substitute(spacetime))) par.model[['spacetime']] <- CheckArg(spacetime, subst, TRUE) if (hasArg('var') && !is.null(subst <- substitute(var))) par.general[['var']] <- CheckArg(var, subst, TRUE) if (hasArg('scale') && !is.null(subst <- substitute(scale))) par.general[['scale']] <- CheckArg(scale, subst, TRUE) if (hasArg('Aniso') && !is.null(subst <- substitute(Aniso))) par.general[['Aniso']] <- CheckArg(Aniso, subst, TRUE) if (hasArg('proj') && !is.null(subst <- substitute(proj))) par.general[['proj']] <- CheckMixed(proj, subst, PROJECTION_NAMES) model <- methods::new('RMmodel', call = cl, name = 'RMave', submodels = submodels, par.model = par.model, par.general = par.general) return(model) } RMave <- new(CLASS_RM, .Data = RMave, type = c('positive definite'), isotropy = c('symmetric'), domain = c('single variable'), operator = TRUE, monotone = 'not monotone', finiterange = FALSE, simpleArguments = TRUE, maxdim = 10, vdim = 1 ) RMbcw <- function(alpha, beta, c, var, scale, Aniso, proj) { cl <- match.call() submodels <- par.general <- par.model <- list() if (hasArg('alpha') && !is.null(subst <- substitute(alpha))) par.model[['alpha']] <- CheckArg(alpha, subst, TRUE) if (hasArg('beta') && !is.null(subst <- substitute(beta))) par.model[['beta']] <- CheckArg(beta, subst, TRUE) if (hasArg('c') && !is.null(subst <- substitute(c))) par.model[['c']] <- CheckArg(c, subst, TRUE) if (hasArg('var') && !is.null(subst <- substitute(var))) par.general[['var']] <- CheckArg(var, subst, TRUE) if (hasArg('scale') && !is.null(subst <- substitute(scale))) par.general[['scale']] <- CheckArg(scale, subst, TRUE) if (hasArg('Aniso') && !is.null(subst <- substitute(Aniso))) par.general[['Aniso']] <- CheckArg(Aniso, subst, TRUE) if (hasArg('proj') && !is.null(subst <- substitute(proj))) par.general[['proj']] <- CheckMixed(proj, subst, PROJECTION_NAMES) model <- methods::new('RMmodel', call = cl, name = 'RMbcw', submodels = submodels, par.model = par.model, par.general = par.general) return(model) } RMbcw <- new(CLASS_RM, .Data = RMbcw, type = c('variogram', 'positive definite', 'tail correlation', 'positive definite'), isotropy = c('isotropic', 'isotropic', 'isotropic', 'spherical isotropic'), domain = c('single variable'), operator = FALSE, monotone = 'normal mixture', finiterange = FALSE, simpleArguments = TRUE, maxdim = Inf, vdim = 1 ) RMlsfbm <- function(alpha, const, var, scale, Aniso, proj) { cl <- match.call() submodels <- par.general <- par.model <- list() if (hasArg('alpha') && !is.null(subst <- substitute(alpha))) par.model[['alpha']] <- CheckArg(alpha, subst, TRUE) if (hasArg('const') && !is.null(subst <- substitute(const))) par.model[['const']] <- CheckArg(const, subst, TRUE) if (hasArg('var') && !is.null(subst <- substitute(var))) par.general[['var']] <- CheckArg(var, subst, TRUE) if (hasArg('scale') && !is.null(subst <- substitute(scale))) par.general[['scale']] <- CheckArg(scale, subst, TRUE) if (hasArg('Aniso') && !is.null(subst <- substitute(Aniso))) par.general[['Aniso']] <- CheckArg(Aniso, subst, TRUE) if (hasArg('proj') && !is.null(subst <- substitute(proj))) par.general[['proj']] <- CheckMixed(proj, subst, PROJECTION_NAMES) model <- methods::new('RMmodel', call = cl, name = 'RMlsfbm', submodels = submodels, par.model = par.model, par.general = par.general) return(model) } RMlsfbm <- new(CLASS_RM, .Data = RMlsfbm, type = c('positive definite'), isotropy = c('isotropic'), domain = c('single variable'), operator = FALSE, monotone = 'monotone', finiterange = FALSE, simpleArguments = TRUE, maxdim = Inf, vdim = 1 ) RMbessel <- function(nu, var, scale, Aniso, proj) { cl <- match.call() submodels <- par.general <- par.model <- list() if (hasArg('nu') && !is.null(subst <- substitute(nu))) par.model[['nu']] <- CheckArg(nu, subst, TRUE) if (hasArg('var') && !is.null(subst <- substitute(var))) par.general[['var']] <- CheckArg(var, subst, TRUE) if (hasArg('scale') && !is.null(subst <- substitute(scale))) par.general[['scale']] <- CheckArg(scale, subst, TRUE) if (hasArg('Aniso') && !is.null(subst <- substitute(Aniso))) par.general[['Aniso']] <- CheckArg(Aniso, subst, TRUE) if (hasArg('proj') && !is.null(subst <- substitute(proj))) par.general[['proj']] <- CheckMixed(proj, subst, PROJECTION_NAMES) model <- methods::new('RMmodel', call = cl, name = 'RMbessel', submodels = submodels, par.model = par.model, par.general = par.general) return(model) } RMbessel <- new(CLASS_RM, .Data = RMbessel, type = c('positive definite'), isotropy = c('isotropic'), domain = c('single variable'), operator = FALSE, monotone = 'not monotone', finiterange = FALSE, simpleArguments = TRUE, maxdim = Inf, vdim = 1 ) RMbigneiting <- function(kappa, mu, s, sred12, gamma, cdiag, rhored, c, var, scale, Aniso, proj) { cl <- match.call() submodels <- par.general <- par.model <- list() if (hasArg('kappa') && !is.null(subst <- substitute(kappa))) par.model[['kappa']] <- CheckArg(kappa, subst, TRUE) if (hasArg('mu') && !is.null(subst <- substitute(mu))) par.model[['mu']] <- CheckArg(mu, subst, TRUE) if (hasArg('s') && !is.null(subst <- substitute(s))) par.model[['s']] <- CheckArg(s, subst, TRUE) if (hasArg('sred12') && !is.null(subst <- substitute(sred12))) par.model[['sred12']] <- CheckArg(sred12, subst, TRUE) if (hasArg('gamma') && !is.null(subst <- substitute(gamma))) par.model[['gamma']] <- CheckArg(gamma, subst, TRUE) if (hasArg('cdiag') && !is.null(subst <- substitute(cdiag))) par.model[['cdiag']] <- CheckArg(cdiag, subst, TRUE) if (hasArg('rhored') && !is.null(subst <- substitute(rhored))) par.model[['rhored']] <- CheckArg(rhored, subst, TRUE) if (hasArg('c') && !is.null(subst <- substitute(c))) par.model[['c']] <- CheckArg(c, subst, TRUE) if (hasArg('var') && !is.null(subst <- substitute(var))) par.general[['var']] <- CheckArg(var, subst, TRUE) if (hasArg('scale') && !is.null(subst <- substitute(scale))) par.general[['scale']] <- CheckArg(scale, subst, TRUE) if (hasArg('Aniso') && !is.null(subst <- substitute(Aniso))) par.general[['Aniso']] <- CheckArg(Aniso, subst, TRUE) if (hasArg('proj') && !is.null(subst <- substitute(proj))) par.general[['proj']] <- CheckMixed(proj, subst, PROJECTION_NAMES) model <- methods::new('RMmodel', call = cl, name = 'RMbigneiting', submodels = submodels, par.model = par.model, par.general = par.general) return(model) } RMbigneiting <- new(CLASS_RM, .Data = RMbigneiting, type = c('positive definite'), isotropy = c('isotropic'), domain = c('single variable'), operator = FALSE, monotone = 'not monotone', finiterange = TRUE, simpleArguments = TRUE, maxdim = -1, vdim = 2 ) RMbernoulli <- function(phi, threshold, correlation, centred, var, scale, Aniso, proj) { cl <- match.call() submodels <- par.general <- par.model <- list() if (hasArg(phi)) submodels[['phi']] <- phi if (hasArg('threshold') && !is.null(subst <- substitute(threshold))) par.model[['threshold']] <- CheckArg(threshold, subst, TRUE) if (hasArg('correlation') && !is.null(subst <- substitute(correlation))) par.model[['correlation']] <- CheckArg(correlation, subst, TRUE) if (hasArg('centred') && !is.null(subst <- substitute(centred))) par.model[['centred']] <- CheckArg(centred, subst, TRUE) if (hasArg('var') && !is.null(subst <- substitute(var))) par.general[['var']] <- CheckArg(var, subst, TRUE) if (hasArg('scale') && !is.null(subst <- substitute(scale))) par.general[['scale']] <- CheckArg(scale, subst, TRUE) if (hasArg('Aniso') && !is.null(subst <- substitute(Aniso))) par.general[['Aniso']] <- CheckArg(Aniso, subst, TRUE) if (hasArg('proj') && !is.null(subst <- substitute(proj))) par.general[['proj']] <- CheckMixed(proj, subst, PROJECTION_NAMES) model <- methods::new('RMmodel', call = cl, name = 'RMbernoulli', submodels = submodels, par.model = par.model, par.general = par.general) return(model) } RMbernoulli <- new(CLASS_RM, .Data = RMbernoulli, type = c('tail correlation'), isotropy = c('submodel dependent'), domain = c('submodel dependent'), operator = TRUE, monotone = 'submodel dependent monotonicity', finiterange = NA, simpleArguments = TRUE, maxdim = -3, vdim = 1 ) RMbiwm <- function(nudiag, nured12, nu, s, cdiag, rhored, c, notinvnu, var, scale, Aniso, proj) { cl <- match.call() submodels <- par.general <- par.model <- list() if (hasArg('nudiag') && !is.null(subst <- substitute(nudiag))) par.model[['nudiag']] <- CheckArg(nudiag, subst, TRUE) if (hasArg('nured12') && !is.null(subst <- substitute(nured12))) par.model[['nured12']] <- CheckArg(nured12, subst, TRUE) if (hasArg('nu') && !is.null(subst <- substitute(nu))) par.model[['nu']] <- CheckArg(nu, subst, TRUE) if (hasArg('s') && !is.null(subst <- substitute(s))) par.model[['s']] <- CheckArg(s, subst, TRUE) if (hasArg('cdiag') && !is.null(subst <- substitute(cdiag))) par.model[['cdiag']] <- CheckArg(cdiag, subst, TRUE) if (hasArg('rhored') && !is.null(subst <- substitute(rhored))) par.model[['rhored']] <- CheckArg(rhored, subst, TRUE) if (hasArg('c') && !is.null(subst <- substitute(c))) par.model[['c']] <- CheckArg(c, subst, TRUE) if (hasArg('notinvnu') && !is.null(subst <- substitute(notinvnu))) par.model[['notinvnu']] <- CheckArg(notinvnu, subst, TRUE) if (hasArg('var') && !is.null(subst <- substitute(var))) par.general[['var']] <- CheckArg(var, subst, TRUE) if (hasArg('scale') && !is.null(subst <- substitute(scale))) par.general[['scale']] <- CheckArg(scale, subst, TRUE) if (hasArg('Aniso') && !is.null(subst <- substitute(Aniso))) par.general[['Aniso']] <- CheckArg(Aniso, subst, TRUE) if (hasArg('proj') && !is.null(subst <- substitute(proj))) par.general[['proj']] <- CheckMixed(proj, subst, PROJECTION_NAMES) model <- methods::new('RMmodel', call = cl, name = 'RMbiwm', submodels = submodels, par.model = par.model, par.general = par.general) return(model) } RMbiwm <- new(CLASS_RM, .Data = RMbiwm, type = c('positive definite'), isotropy = c('isotropic'), domain = c('single variable'), operator = FALSE, monotone = 'not monotone', finiterange = FALSE, simpleArguments = TRUE, maxdim = Inf, vdim = 2 ) RMbistable <- function(alpha, s, cdiag, rho, rhored, betared, alphadiag, var, scale, Aniso, proj) { cl <- match.call() submodels <- par.general <- par.model <- list() if (hasArg('alpha') && !is.null(subst <- substitute(alpha))) par.model[['alpha']] <- CheckArg(alpha, subst, TRUE) if (hasArg('s') && !is.null(subst <- substitute(s))) par.model[['s']] <- CheckArg(s, subst, TRUE) if (hasArg('cdiag') && !is.null(subst <- substitute(cdiag))) par.model[['cdiag']] <- CheckArg(cdiag, subst, TRUE) if (hasArg('rho') && !is.null(subst <- substitute(rho))) par.model[['rho']] <- CheckArg(rho, subst, TRUE) if (hasArg('rhored') && !is.null(subst <- substitute(rhored))) par.model[['rhored']] <- CheckArg(rhored, subst, TRUE) if (hasArg('betared') && !is.null(subst <- substitute(betared))) par.model[['betared']] <- CheckArg(betared, subst, TRUE) if (hasArg('alphadiag') && !is.null(subst <- substitute(alphadiag))) par.model[['alphadiag']] <- CheckArg(alphadiag, subst, TRUE) if (hasArg('var') && !is.null(subst <- substitute(var))) par.general[['var']] <- CheckArg(var, subst, TRUE) if (hasArg('scale') && !is.null(subst <- substitute(scale))) par.general[['scale']] <- CheckArg(scale, subst, TRUE) if (hasArg('Aniso') && !is.null(subst <- substitute(Aniso))) par.general[['Aniso']] <- CheckArg(Aniso, subst, TRUE) if (hasArg('proj') && !is.null(subst <- substitute(proj))) par.general[['proj']] <- CheckMixed(proj, subst, PROJECTION_NAMES) model <- methods::new('RMmodel', call = cl, name = 'RMbistable', submodels = submodels, par.model = par.model, par.general = par.general) return(model) } RMbistable <- new(CLASS_RM, .Data = RMbistable, type = c('positive definite'), isotropy = c('isotropic'), domain = c('single variable'), operator = FALSE, monotone = 'monotone', finiterange = FALSE, simpleArguments = TRUE, maxdim = 3, vdim = 2 ) RMblend <- function(multi, blend, thresholds, var, scale, Aniso, proj) { cl <- match.call() submodels <- par.general <- par.model <- list() if (hasArg(multi)) submodels[['multi']] <- multi if (hasArg(blend)) submodels[['blend']] <- blend if (hasArg('thresholds') && !is.null(subst <- substitute(thresholds))) par.model[['thresholds']] <- CheckArg(thresholds, subst, TRUE) if (hasArg('var') && !is.null(subst <- substitute(var))) par.general[['var']] <- CheckArg(var, subst, TRUE) if (hasArg('scale') && !is.null(subst <- substitute(scale))) par.general[['scale']] <- CheckArg(scale, subst, TRUE) if (hasArg('Aniso') && !is.null(subst <- substitute(Aniso))) par.general[['Aniso']] <- CheckArg(Aniso, subst, TRUE) if (hasArg('proj') && !is.null(subst <- substitute(proj))) par.general[['proj']] <- CheckMixed(proj, subst, PROJECTION_NAMES) model <- methods::new('RMmodel', call = cl, name = 'RMblend', submodels = submodels, par.model = par.model, par.general = par.general) return(model) } RMblend <- new(CLASS_RM, .Data = RMblend, type = c('positive definite'), isotropy = c('symmetric'), domain = c('kernel'), operator = TRUE, monotone = 'not monotone', finiterange = FALSE, simpleArguments = TRUE, maxdim = -3, vdim = 1 ) RMbrownresnick <- function(phi, var, scale, Aniso, proj) { cl <- match.call() submodels <- par.general <- par.model <- list() if (hasArg(phi)) submodels[['phi']] <- phi if (hasArg('var') && !is.null(subst <- substitute(var))) par.general[['var']] <- CheckArg(var, subst, TRUE) if (hasArg('scale') && !is.null(subst <- substitute(scale))) par.general[['scale']] <- CheckArg(scale, subst, TRUE) if (hasArg('Aniso') && !is.null(subst <- substitute(Aniso))) par.general[['Aniso']] <- CheckArg(Aniso, subst, TRUE) if (hasArg('proj') && !is.null(subst <- substitute(proj))) par.general[['proj']] <- CheckMixed(proj, subst, PROJECTION_NAMES) model <- methods::new('RMmodel', call = cl, name = 'RMbrownresnick', submodels = submodels, par.model = par.model, par.general = par.general) return(model) } RMbrownresnick <- new(CLASS_RM, .Data = RMbrownresnick, type = c('tail correlation'), isotropy = c('submodel dependent'), domain = c('single variable'), operator = TRUE, monotone = 'submodel dependent monotonicity', finiterange = FALSE, simpleArguments = TRUE, maxdim = -3, vdim = 1 ) RMbr2bg <- function(phi, var, scale, Aniso, proj) { cl <- match.call() submodels <- par.general <- par.model <- list() if (hasArg(phi)) submodels[['phi']] <- phi if (hasArg('var') && !is.null(subst <- substitute(var))) par.general[['var']] <- CheckArg(var, subst, TRUE) if (hasArg('scale') && !is.null(subst <- substitute(scale))) par.general[['scale']] <- CheckArg(scale, subst, TRUE) if (hasArg('Aniso') && !is.null(subst <- substitute(Aniso))) par.general[['Aniso']] <- CheckArg(Aniso, subst, TRUE) if (hasArg('proj') && !is.null(subst <- substitute(proj))) par.general[['proj']] <- CheckMixed(proj, subst, PROJECTION_NAMES) model <- methods::new('RMmodel', call = cl, name = 'RMbr2bg', submodels = submodels, par.model = par.model, par.general = par.general) return(model) } RMbr2bg <- new(CLASS_RM, .Data = RMbr2bg, type = c('positive definite'), isotropy = c('submodel dependent'), domain = c('single variable'), operator = TRUE, monotone = 'submodel dependent monotonicity', finiterange = FALSE, simpleArguments = TRUE, maxdim = -3, vdim = 1 ) RMbr2eg <- function(phi, var, scale, Aniso, proj) { cl <- match.call() submodels <- par.general <- par.model <- list() if (hasArg(phi)) submodels[['phi']] <- phi if (hasArg('var') && !is.null(subst <- substitute(var))) par.general[['var']] <- CheckArg(var, subst, TRUE) if (hasArg('scale') && !is.null(subst <- substitute(scale))) par.general[['scale']] <- CheckArg(scale, subst, TRUE) if (hasArg('Aniso') && !is.null(subst <- substitute(Aniso))) par.general[['Aniso']] <- CheckArg(Aniso, subst, TRUE) if (hasArg('proj') && !is.null(subst <- substitute(proj))) par.general[['proj']] <- CheckMixed(proj, subst, PROJECTION_NAMES) model <- methods::new('RMmodel', call = cl, name = 'RMbr2eg', submodels = submodels, par.model = par.model, par.general = par.general) return(model) } RMbr2eg <- new(CLASS_RM, .Data = RMbr2eg, type = c('positive definite'), isotropy = c('submodel dependent'), domain = c('single variable'), operator = TRUE, monotone = 'submodel dependent monotonicity', finiterange = FALSE, simpleArguments = TRUE, maxdim = -3, vdim = 1 ) RMbubble <- function(phi, scaling, z, weight, minscale, barycentre, var, scale, Aniso, proj) { cl <- match.call() submodels <- par.general <- par.model <- list() if (hasArg(phi)) submodels[['phi']] <- phi if (hasArg(scaling)) submodels[['scaling']] <- scaling if (hasArg('z') && !is.null(subst <- substitute(z))) par.model[['z']] <- CheckArg(z, subst, TRUE) if (hasArg('weight') && !is.null(subst <- substitute(weight))) par.model[['weight']] <- CheckArg(weight, subst, TRUE) if (hasArg('minscale') && !is.null(subst <- substitute(minscale))) par.model[['minscale']] <- CheckArg(minscale, subst, TRUE) if (hasArg('barycentre') && !is.null(subst <- substitute(barycentre))) par.model[['barycentre']] <- CheckArg(barycentre, subst, TRUE) if (hasArg('var') && !is.null(subst <- substitute(var))) par.general[['var']] <- CheckArg(var, subst, TRUE) if (hasArg('scale') && !is.null(subst <- substitute(scale))) par.general[['scale']] <- CheckArg(scale, subst, TRUE) if (hasArg('Aniso') && !is.null(subst <- substitute(Aniso))) par.general[['Aniso']] <- CheckArg(Aniso, subst, TRUE) if (hasArg('proj') && !is.null(subst <- substitute(proj))) par.general[['proj']] <- CheckMixed(proj, subst, PROJECTION_NAMES) model <- methods::new('RMmodel', call = cl, name = 'RMbubble', submodels = submodels, par.model = par.model, par.general = par.general) return(model) } RMbubble <- new(CLASS_RM, .Data = RMbubble, type = c('positive definite'), isotropy = c('non-dimension-reducing'), domain = c('kernel'), operator = TRUE, monotone = 'not monotone', finiterange = FALSE, simpleArguments = TRUE, maxdim = Inf, vdim = 1 ) RMcauchy <- function(gamma, var, scale, Aniso, proj) { cl <- match.call() submodels <- par.general <- par.model <- list() if (hasArg('gamma') && !is.null(subst <- substitute(gamma))) par.model[['gamma']] <- CheckArg(gamma, subst, TRUE) if (hasArg('var') && !is.null(subst <- substitute(var))) par.general[['var']] <- CheckArg(var, subst, TRUE) if (hasArg('scale') && !is.null(subst <- substitute(scale))) par.general[['scale']] <- CheckArg(scale, subst, TRUE) if (hasArg('Aniso') && !is.null(subst <- substitute(Aniso))) par.general[['Aniso']] <- CheckArg(Aniso, subst, TRUE) if (hasArg('proj') && !is.null(subst <- substitute(proj))) par.general[['proj']] <- CheckMixed(proj, subst, PROJECTION_NAMES) model <- methods::new('RMmodel', call = cl, name = 'RMcauchy', submodels = submodels, par.model = par.model, par.general = par.general) return(model) } RMcauchy <- new(CLASS_RM, .Data = RMcauchy, type = c('positive definite'), isotropy = c('isotropic'), domain = c('single variable'), operator = FALSE, monotone = 'normal mixture', finiterange = FALSE, simpleArguments = TRUE, maxdim = Inf, vdim = 1 ) RMcircular <- function(var, scale, Aniso, proj) { cl <- match.call() submodels <- par.general <- par.model <- list() if (hasArg('var') && !is.null(subst <- substitute(var))) par.general[['var']] <- CheckArg(var, subst, TRUE) if (hasArg('scale') && !is.null(subst <- substitute(scale))) par.general[['scale']] <- CheckArg(scale, subst, TRUE) if (hasArg('Aniso') && !is.null(subst <- substitute(Aniso))) par.general[['Aniso']] <- CheckArg(Aniso, subst, TRUE) if (hasArg('proj') && !is.null(subst <- substitute(proj))) par.general[['proj']] <- CheckMixed(proj, subst, PROJECTION_NAMES) model <- methods::new('RMmodel', call = cl, name = 'RMcircular', submodels = submodels, par.model = par.model, par.general = par.general) return(model) } RMcircular <- new(CLASS_RM, .Data = RMcircular, type = c('tail correlation'), isotropy = c('isotropic'), domain = c('single variable'), operator = FALSE, monotone = 'Gneiting-Schaback class', finiterange = FALSE, simpleArguments = TRUE, maxdim = 2, vdim = 1 ) RMconstant <- function(M, var) { cl <- match.call() submodels <- par.general <- par.model <- list() if (hasArg('M') && !is.null(subst <- substitute(M))) par.model[['M']] <- CheckArg(M, subst, TRUE) if (hasArg('var') && !is.null(subst <- substitute(var))) par.general[['var']] <- CheckArg(var, subst, TRUE) model <- methods::new('RMmodel', call = cl, name = 'RMconstant', submodels = submodels, par.model = par.model, par.general = par.general) return(model) } RMconstant <- new(CLASS_RM, .Data = RMconstant, type = c('positive definite', 'negative definite'), isotropy = c('framework dependent', 'isotropic'), domain = c('single variable'), operator = FALSE, monotone = 'submodel dependent monotonicity', finiterange = FALSE, simpleArguments = TRUE, maxdim = Inf, vdim = -1 ) iRMfixcov <- function(norm, M, x, raw, var, proj) { cl <- match.call() submodels <- par.general <- par.model <- list() if (hasArg(norm)) submodels[['norm']] <- norm if (hasArg('M') && !is.null(subst <- substitute(M))) par.model[['M']] <- CheckArg(M, subst, TRUE) if (hasArg('x') && !is.null(subst <- substitute(x))) par.model[['x']] <- CheckArg(x, subst, TRUE) if (hasArg('raw') && !is.null(subst <- substitute(raw))) par.model[['raw']] <- CheckArg(raw, subst, TRUE) if (hasArg('var') && !is.null(subst <- substitute(var))) par.general[['var']] <- CheckArg(var, subst, TRUE) if (hasArg('proj') && !is.null(subst <- substitute(proj))) par.general[['proj']] <- CheckMixed(proj, subst, PROJECTION_NAMES) model <- methods::new('RMmodel', call = cl, name = 'RMfixcov', submodels = submodels, par.model = par.model, par.general = par.general) return(model) } iRMfixcov <- new(CLASS_RM, .Data = iRMfixcov, type = c('positive definite', 'positive definite', 'positive definite'), isotropy = c('non-dimension-reducing', 'isotropic', 'earth isotropic'), domain = c('kernel'), operator = TRUE, monotone = 'not monotone', finiterange = FALSE, simpleArguments = FALSE, maxdim = Inf, vdim = -1 ) RMcoxisham <- function(phi, mu, D, beta, var, scale, Aniso, proj) { cl <- match.call() submodels <- par.general <- par.model <- list() if (hasArg(phi)) submodels[['phi']] <- phi if (hasArg('mu') && !is.null(subst <- substitute(mu))) par.model[['mu']] <- CheckArg(mu, subst, TRUE) if (hasArg('D') && !is.null(subst <- substitute(D))) par.model[['D']] <- CheckArg(D, subst, TRUE) if (hasArg('beta') && !is.null(subst <- substitute(beta))) par.model[['beta']] <- CheckArg(beta, subst, TRUE) if (hasArg('var') && !is.null(subst <- substitute(var))) par.general[['var']] <- CheckArg(var, subst, TRUE) if (hasArg('scale') && !is.null(subst <- substitute(scale))) par.general[['scale']] <- CheckArg(scale, subst, TRUE) if (hasArg('Aniso') && !is.null(subst <- substitute(Aniso))) par.general[['Aniso']] <- CheckArg(Aniso, subst, TRUE) if (hasArg('proj') && !is.null(subst <- substitute(proj))) par.general[['proj']] <- CheckMixed(proj, subst, PROJECTION_NAMES) model <- methods::new('RMmodel', call = cl, name = 'RMcoxisham', submodels = submodels, par.model = par.model, par.general = par.general) return(model) } RMcoxisham <- new(CLASS_RM, .Data = RMcoxisham, type = c('positive definite'), isotropy = c('symmetric'), domain = c('single variable'), operator = TRUE, monotone = 'not monotone', finiterange = FALSE, simpleArguments = TRUE, maxdim = 3, vdim = 1 ) RMcubic <- function(var, scale, Aniso, proj) { cl <- match.call() submodels <- par.general <- par.model <- list() if (hasArg('var') && !is.null(subst <- substitute(var))) par.general[['var']] <- CheckArg(var, subst, TRUE) if (hasArg('scale') && !is.null(subst <- substitute(scale))) par.general[['scale']] <- CheckArg(scale, subst, TRUE) if (hasArg('Aniso') && !is.null(subst <- substitute(Aniso))) par.general[['Aniso']] <- CheckArg(Aniso, subst, TRUE) if (hasArg('proj') && !is.null(subst <- substitute(proj))) par.general[['proj']] <- CheckMixed(proj, subst, PROJECTION_NAMES) model <- methods::new('RMmodel', call = cl, name = 'RMcubic', submodels = submodels, par.model = par.model, par.general = par.general) return(model) } RMcubic <- new(CLASS_RM, .Data = RMcubic, type = c('tail correlation'), isotropy = c('isotropic'), domain = c('single variable'), operator = FALSE, monotone = 'monotone', finiterange = FALSE, simpleArguments = TRUE, maxdim = 3, vdim = 1 ) RMcurlfree <- function(phi, which, var, scale, Aniso, proj) { cl <- match.call() submodels <- par.general <- par.model <- list() if (hasArg(phi)) submodels[['phi']] <- phi if (hasArg('which') && !is.null(subst <- substitute(which))) par.model[['which']] <- CheckArg(which, subst, TRUE) if (hasArg('var') && !is.null(subst <- substitute(var))) par.general[['var']] <- CheckArg(var, subst, TRUE) if (hasArg('scale') && !is.null(subst <- substitute(scale))) par.general[['scale']] <- CheckArg(scale, subst, TRUE) if (hasArg('Aniso') && !is.null(subst <- substitute(Aniso))) par.general[['Aniso']] <- CheckArg(Aniso, subst, TRUE) if (hasArg('proj') && !is.null(subst <- substitute(proj))) par.general[['proj']] <- CheckMixed(proj, subst, PROJECTION_NAMES) model <- methods::new('RMmodel', call = cl, name = 'RMcurlfree', submodels = submodels, par.model = par.model, par.general = par.general) return(model) } RMcurlfree <- new(CLASS_RM, .Data = RMcurlfree, type = c('positive definite'), isotropy = c('cartesian system'), domain = c('single variable'), operator = TRUE, monotone = 'not monotone', finiterange = NA, simpleArguments = TRUE, maxdim = -3, vdim = -1 ) RMcutoff <- function(phi, diameter, a, var, scale, Aniso, proj) { cl <- match.call() submodels <- par.general <- par.model <- list() if (hasArg(phi)) submodels[['phi']] <- phi if (hasArg('diameter') && !is.null(subst <- substitute(diameter))) par.model[['diameter']] <- CheckArg(diameter, subst, TRUE) if (hasArg('a') && !is.null(subst <- substitute(a))) par.model[['a']] <- CheckArg(a, subst, TRUE) if (hasArg('var') && !is.null(subst <- substitute(var))) par.general[['var']] <- CheckArg(var, subst, TRUE) if (hasArg('scale') && !is.null(subst <- substitute(scale))) par.general[['scale']] <- CheckArg(scale, subst, TRUE) if (hasArg('Aniso') && !is.null(subst <- substitute(Aniso))) par.general[['Aniso']] <- CheckArg(Aniso, subst, TRUE) if (hasArg('proj') && !is.null(subst <- substitute(proj))) par.general[['proj']] <- CheckMixed(proj, subst, PROJECTION_NAMES) model <- methods::new('RMmodel', call = cl, name = 'RMcutoff', submodels = submodels, par.model = par.model, par.general = par.general) return(model) } RMcutoff <- new(CLASS_RM, .Data = RMcutoff, type = c('positive definite'), isotropy = c('isotropic'), domain = c('single variable'), operator = TRUE, monotone = 'monotone', finiterange = TRUE, simpleArguments = TRUE, maxdim = 13, vdim = -3 ) RMdagum <- function(beta, gamma, var, scale, Aniso, proj) { cl <- match.call() submodels <- par.general <- par.model <- list() if (hasArg('beta') && !is.null(subst <- substitute(beta))) par.model[['beta']] <- CheckArg(beta, subst, TRUE) if (hasArg('gamma') && !is.null(subst <- substitute(gamma))) par.model[['gamma']] <- CheckArg(gamma, subst, TRUE) if (hasArg('var') && !is.null(subst <- substitute(var))) par.general[['var']] <- CheckArg(var, subst, TRUE) if (hasArg('scale') && !is.null(subst <- substitute(scale))) par.general[['scale']] <- CheckArg(scale, subst, TRUE) if (hasArg('Aniso') && !is.null(subst <- substitute(Aniso))) par.general[['Aniso']] <- CheckArg(Aniso, subst, TRUE) if (hasArg('proj') && !is.null(subst <- substitute(proj))) par.general[['proj']] <- CheckMixed(proj, subst, PROJECTION_NAMES) model <- methods::new('RMmodel', call = cl, name = 'RMdagum', submodels = submodels, par.model = par.model, par.general = par.general) return(model) } RMdagum <- new(CLASS_RM, .Data = RMdagum, type = c('positive definite', 'tail correlation', 'positive definite'), isotropy = c('isotropic', 'isotropic', 'spherical isotropic'), domain = c('single variable'), operator = FALSE, monotone = 'parameter dependent monotonicity', finiterange = FALSE, simpleArguments = TRUE, maxdim = Inf, vdim = 1 ) RMdampedcos <- function(lambda, var, scale, Aniso, proj) { cl <- match.call() submodels <- par.general <- par.model <- list() if (hasArg('lambda') && !is.null(subst <- substitute(lambda))) par.model[['lambda']] <- CheckArg(lambda, subst, TRUE) if (hasArg('var') && !is.null(subst <- substitute(var))) par.general[['var']] <- CheckArg(var, subst, TRUE) if (hasArg('scale') && !is.null(subst <- substitute(scale))) par.general[['scale']] <- CheckArg(scale, subst, TRUE) if (hasArg('Aniso') && !is.null(subst <- substitute(Aniso))) par.general[['Aniso']] <- CheckArg(Aniso, subst, TRUE) if (hasArg('proj') && !is.null(subst <- substitute(proj))) par.general[['proj']] <- CheckMixed(proj, subst, PROJECTION_NAMES) model <- methods::new('RMmodel', call = cl, name = 'RMdampedcos', submodels = submodels, par.model = par.model, par.general = par.general) return(model) } RMdampedcos <- new(CLASS_RM, .Data = RMdampedcos, type = c('positive definite'), isotropy = c('isotropic'), domain = c('single variable'), operator = FALSE, monotone = 'not monotone', finiterange = FALSE, simpleArguments = TRUE, maxdim = -1, vdim = 1 ) RMderiv <- function(phi, which, var, scale, Aniso, proj) { cl <- match.call() submodels <- par.general <- par.model <- list() if (hasArg(phi)) submodels[['phi']] <- phi if (hasArg('which') && !is.null(subst <- substitute(which))) par.model[['which']] <- CheckArg(which, subst, TRUE) if (hasArg('var') && !is.null(subst <- substitute(var))) par.general[['var']] <- CheckArg(var, subst, TRUE) if (hasArg('scale') && !is.null(subst <- substitute(scale))) par.general[['scale']] <- CheckArg(scale, subst, TRUE) if (hasArg('Aniso') && !is.null(subst <- substitute(Aniso))) par.general[['Aniso']] <- CheckArg(Aniso, subst, TRUE) if (hasArg('proj') && !is.null(subst <- substitute(proj))) par.general[['proj']] <- CheckMixed(proj, subst, PROJECTION_NAMES) model <- methods::new('RMmodel', call = cl, name = 'RMderiv', submodels = submodels, par.model = par.model, par.general = par.general) return(model) } RMderiv <- new(CLASS_RM, .Data = RMderiv, type = c('positive definite'), isotropy = c('cartesian system'), domain = c('single variable'), operator = TRUE, monotone = 'not monotone', finiterange = NA, simpleArguments = TRUE, maxdim = -3, vdim = -1 ) RMdewijsian <- function(alpha, var, scale, Aniso, proj) { cl <- match.call() submodels <- par.general <- par.model <- list() if (hasArg('alpha') && !is.null(subst <- substitute(alpha))) par.model[['alpha']] <- CheckArg(alpha, subst, TRUE) if (hasArg('var') && !is.null(subst <- substitute(var))) par.general[['var']] <- CheckArg(var, subst, TRUE) if (hasArg('scale') && !is.null(subst <- substitute(scale))) par.general[['scale']] <- CheckArg(scale, subst, TRUE) if (hasArg('Aniso') && !is.null(subst <- substitute(Aniso))) par.general[['Aniso']] <- CheckArg(Aniso, subst, TRUE) if (hasArg('proj') && !is.null(subst <- substitute(proj))) par.general[['proj']] <- CheckMixed(proj, subst, PROJECTION_NAMES) model <- methods::new('RMmodel', call = cl, name = 'RMdewijsian', submodels = submodels, par.model = par.model, par.general = par.general) return(model) } RMdewijsian <- new(CLASS_RM, .Data = RMdewijsian, type = c('variogram'), isotropy = c('isotropic'), domain = c('single variable'), operator = FALSE, monotone = 'monotone', finiterange = FALSE, simpleArguments = TRUE, maxdim = Inf, vdim = 1 ) RMdivfree <- function(phi, which, var, scale, Aniso, proj) { cl <- match.call() submodels <- par.general <- par.model <- list() if (hasArg(phi)) submodels[['phi']] <- phi if (hasArg('which') && !is.null(subst <- substitute(which))) par.model[['which']] <- CheckArg(which, subst, TRUE) if (hasArg('var') && !is.null(subst <- substitute(var))) par.general[['var']] <- CheckArg(var, subst, TRUE) if (hasArg('scale') && !is.null(subst <- substitute(scale))) par.general[['scale']] <- CheckArg(scale, subst, TRUE) if (hasArg('Aniso') && !is.null(subst <- substitute(Aniso))) par.general[['Aniso']] <- CheckArg(Aniso, subst, TRUE) if (hasArg('proj') && !is.null(subst <- substitute(proj))) par.general[['proj']] <- CheckMixed(proj, subst, PROJECTION_NAMES) model <- methods::new('RMmodel', call = cl, name = 'RMdivfree', submodels = submodels, par.model = par.model, par.general = par.general) return(model) } RMdivfree <- new(CLASS_RM, .Data = RMdivfree, type = c('positive definite'), isotropy = c('cartesian system'), domain = c('single variable'), operator = TRUE, monotone = 'not monotone', finiterange = NA, simpleArguments = TRUE, maxdim = -3, vdim = -1 ) RMepscauchy <- function(alpha, beta, eps, var, scale, Aniso, proj) { cl <- match.call() submodels <- par.general <- par.model <- list() if (hasArg('alpha') && !is.null(subst <- substitute(alpha))) par.model[['alpha']] <- CheckArg(alpha, subst, TRUE) if (hasArg('beta') && !is.null(subst <- substitute(beta))) par.model[['beta']] <- CheckArg(beta, subst, TRUE) if (hasArg('eps') && !is.null(subst <- substitute(eps))) par.model[['eps']] <- CheckArg(eps, subst, TRUE) if (hasArg('var') && !is.null(subst <- substitute(var))) par.general[['var']] <- CheckArg(var, subst, TRUE) if (hasArg('scale') && !is.null(subst <- substitute(scale))) par.general[['scale']] <- CheckArg(scale, subst, TRUE) if (hasArg('Aniso') && !is.null(subst <- substitute(Aniso))) par.general[['Aniso']] <- CheckArg(Aniso, subst, TRUE) if (hasArg('proj') && !is.null(subst <- substitute(proj))) par.general[['proj']] <- CheckMixed(proj, subst, PROJECTION_NAMES) model <- methods::new('RMmodel', call = cl, name = 'RMepscauchy', submodels = submodels, par.model = par.model, par.general = par.general) return(model) } RMepscauchy <- new(CLASS_RM, .Data = RMepscauchy, type = c('positive definite'), isotropy = c('isotropic'), domain = c('single variable'), operator = FALSE, monotone = 'normal mixture', finiterange = FALSE, simpleArguments = TRUE, maxdim = Inf, vdim = 1 ) RMexp <- function(var, scale, Aniso, proj) { cl <- match.call() submodels <- par.general <- par.model <- list() if (hasArg('var') && !is.null(subst <- substitute(var))) par.general[['var']] <- CheckArg(var, subst, TRUE) if (hasArg('scale') && !is.null(subst <- substitute(scale))) par.general[['scale']] <- CheckArg(scale, subst, TRUE) if (hasArg('Aniso') && !is.null(subst <- substitute(Aniso))) par.general[['Aniso']] <- CheckArg(Aniso, subst, TRUE) if (hasArg('proj') && !is.null(subst <- substitute(proj))) par.general[['proj']] <- CheckMixed(proj, subst, PROJECTION_NAMES) model <- methods::new('RMmodel', call = cl, name = 'RMexp', submodels = submodels, par.model = par.model, par.general = par.general) return(model) } RMexp <- new(CLASS_RM, .Data = RMexp, type = c('tail correlation', 'positive definite'), isotropy = c('isotropic', 'spherical isotropic'), domain = c('single variable'), operator = FALSE, monotone = 'completely monotone', finiterange = FALSE, simpleArguments = TRUE, maxdim = Inf, vdim = 1 ) RMexponential <- function(phi, n, standardised, var, scale, Aniso, proj) { cl <- match.call() submodels <- par.general <- par.model <- list() if (hasArg(phi)) submodels[['phi']] <- phi if (hasArg('n') && !is.null(subst <- substitute(n))) par.model[['n']] <- CheckArg(n, subst, TRUE) if (hasArg('standardised') && !is.null(subst <- substitute(standardised))) par.model[['standardised']] <- CheckArg(standardised, subst, TRUE) if (hasArg('var') && !is.null(subst <- substitute(var))) par.general[['var']] <- CheckArg(var, subst, TRUE) if (hasArg('scale') && !is.null(subst <- substitute(scale))) par.general[['scale']] <- CheckArg(scale, subst, TRUE) if (hasArg('Aniso') && !is.null(subst <- substitute(Aniso))) par.general[['Aniso']] <- CheckArg(Aniso, subst, TRUE) if (hasArg('proj') && !is.null(subst <- substitute(proj))) par.general[['proj']] <- CheckMixed(proj, subst, PROJECTION_NAMES) model <- methods::new('RMmodel', call = cl, name = 'RMexponential', submodels = submodels, par.model = par.model, par.general = par.general) return(model) } RMexponential <- new(CLASS_RM, .Data = RMexponential, type = c('positive definite'), isotropy = c('submodel dependent'), domain = c('submodel dependent'), operator = TRUE, monotone = 'not monotone', finiterange = FALSE, simpleArguments = TRUE, maxdim = -3, vdim = 1 ) RMschlather <- function(phi, var, scale, Aniso, proj) { cl <- match.call() submodels <- par.general <- par.model <- list() if (hasArg(phi)) submodels[['phi']] <- phi if (hasArg('var') && !is.null(subst <- substitute(var))) par.general[['var']] <- CheckArg(var, subst, TRUE) if (hasArg('scale') && !is.null(subst <- substitute(scale))) par.general[['scale']] <- CheckArg(scale, subst, TRUE) if (hasArg('Aniso') && !is.null(subst <- substitute(Aniso))) par.general[['Aniso']] <- CheckArg(Aniso, subst, TRUE) if (hasArg('proj') && !is.null(subst <- substitute(proj))) par.general[['proj']] <- CheckMixed(proj, subst, PROJECTION_NAMES) model <- methods::new('RMmodel', call = cl, name = 'RMschlather', submodels = submodels, par.model = par.model, par.general = par.general) return(model) } RMschlather <- new(CLASS_RM, .Data = RMschlather, type = c('tail correlation'), isotropy = c('submodel dependent'), domain = c('single variable'), operator = TRUE, monotone = 'not monotone', finiterange = NA, simpleArguments = TRUE, maxdim = -3, vdim = 1 ) RMfractdiff <- function(a, var, scale, Aniso, proj) { cl <- match.call() submodels <- par.general <- par.model <- list() if (hasArg('a') && !is.null(subst <- substitute(a))) par.model[['a']] <- CheckArg(a, subst, TRUE) if (hasArg('var') && !is.null(subst <- substitute(var))) par.general[['var']] <- CheckArg(var, subst, TRUE) if (hasArg('scale') && !is.null(subst <- substitute(scale))) par.general[['scale']] <- CheckArg(scale, subst, TRUE) if (hasArg('Aniso') && !is.null(subst <- substitute(Aniso))) par.general[['Aniso']] <- CheckArg(Aniso, subst, TRUE) if (hasArg('proj') && !is.null(subst <- substitute(proj))) par.general[['proj']] <- CheckMixed(proj, subst, PROJECTION_NAMES) model <- methods::new('RMmodel', call = cl, name = 'RMfractdiff', submodels = submodels, par.model = par.model, par.general = par.general) return(model) } RMfractdiff <- new(CLASS_RM, .Data = RMfractdiff, type = c('positive definite'), isotropy = c('isotropic'), domain = c('single variable'), operator = FALSE, monotone = 'not monotone', finiterange = FALSE, simpleArguments = TRUE, maxdim = 1, vdim = 1 ) RMflatpower <- function(alpha, var, scale, Aniso, proj) { cl <- match.call() submodels <- par.general <- par.model <- list() if (hasArg('alpha') && !is.null(subst <- substitute(alpha))) par.model[['alpha']] <- CheckArg(alpha, subst, TRUE) if (hasArg('var') && !is.null(subst <- substitute(var))) par.general[['var']] <- CheckArg(var, subst, TRUE) if (hasArg('scale') && !is.null(subst <- substitute(scale))) par.general[['scale']] <- CheckArg(scale, subst, TRUE) if (hasArg('Aniso') && !is.null(subst <- substitute(Aniso))) par.general[['Aniso']] <- CheckArg(Aniso, subst, TRUE) if (hasArg('proj') && !is.null(subst <- substitute(proj))) par.general[['proj']] <- CheckMixed(proj, subst, PROJECTION_NAMES) model <- methods::new('RMmodel', call = cl, name = 'RMflatpower', submodels = submodels, par.model = par.model, par.general = par.general) return(model) } RMflatpower <- new(CLASS_RM, .Data = RMflatpower, type = c('variogram'), isotropy = c('isotropic'), domain = c('single variable'), operator = FALSE, monotone = 'Bernstein', finiterange = FALSE, simpleArguments = TRUE, maxdim = Inf, vdim = 1 ) RMfbm <- function(alpha, var, scale, Aniso, proj) { cl <- match.call() submodels <- par.general <- par.model <- list() if (hasArg('alpha') && !is.null(subst <- substitute(alpha))) par.model[['alpha']] <- CheckArg(alpha, subst, TRUE) if (hasArg('var') && !is.null(subst <- substitute(var))) par.general[['var']] <- CheckArg(var, subst, TRUE) if (hasArg('scale') && !is.null(subst <- substitute(scale))) par.general[['scale']] <- CheckArg(scale, subst, TRUE) if (hasArg('Aniso') && !is.null(subst <- substitute(Aniso))) par.general[['Aniso']] <- CheckArg(Aniso, subst, TRUE) if (hasArg('proj') && !is.null(subst <- substitute(proj))) par.general[['proj']] <- CheckMixed(proj, subst, PROJECTION_NAMES) model <- methods::new('RMmodel', call = cl, name = 'RMfbm', submodels = submodels, par.model = par.model, par.general = par.general) return(model) } RMfbm <- new(CLASS_RM, .Data = RMfbm, type = c('variogram'), isotropy = c('isotropic'), domain = c('single variable'), operator = FALSE, monotone = 'Bernstein', finiterange = FALSE, simpleArguments = TRUE, maxdim = Inf, vdim = 1 ) RMfractgauss <- function(alpha, var, scale, Aniso, proj) { cl <- match.call() submodels <- par.general <- par.model <- list() if (hasArg('alpha') && !is.null(subst <- substitute(alpha))) par.model[['alpha']] <- CheckArg(alpha, subst, TRUE) if (hasArg('var') && !is.null(subst <- substitute(var))) par.general[['var']] <- CheckArg(var, subst, TRUE) if (hasArg('scale') && !is.null(subst <- substitute(scale))) par.general[['scale']] <- CheckArg(scale, subst, TRUE) if (hasArg('Aniso') && !is.null(subst <- substitute(Aniso))) par.general[['Aniso']] <- CheckArg(Aniso, subst, TRUE) if (hasArg('proj') && !is.null(subst <- substitute(proj))) par.general[['proj']] <- CheckMixed(proj, subst, PROJECTION_NAMES) model <- methods::new('RMmodel', call = cl, name = 'RMfractgauss', submodels = submodels, par.model = par.model, par.general = par.general) return(model) } RMfractgauss <- new(CLASS_RM, .Data = RMfractgauss, type = c('positive definite'), isotropy = c('isotropic'), domain = c('single variable'), operator = FALSE, monotone = 'not monotone', finiterange = FALSE, simpleArguments = TRUE, maxdim = 1, vdim = 1 ) RMgauss <- function(var, scale, Aniso, proj) { cl <- match.call() submodels <- par.general <- par.model <- list() if (hasArg('var') && !is.null(subst <- substitute(var))) par.general[['var']] <- CheckArg(var, subst, TRUE) if (hasArg('scale') && !is.null(subst <- substitute(scale))) par.general[['scale']] <- CheckArg(scale, subst, TRUE) if (hasArg('Aniso') && !is.null(subst <- substitute(Aniso))) par.general[['Aniso']] <- CheckArg(Aniso, subst, TRUE) if (hasArg('proj') && !is.null(subst <- substitute(proj))) par.general[['proj']] <- CheckMixed(proj, subst, PROJECTION_NAMES) model <- methods::new('RMmodel', call = cl, name = 'RMgauss', submodels = submodels, par.model = par.model, par.general = par.general) return(model) } RMgauss <- new(CLASS_RM, .Data = RMgauss, type = c('positive definite'), isotropy = c('isotropic'), domain = c('single variable'), operator = FALSE, monotone = 'normal mixture', finiterange = FALSE, simpleArguments = TRUE, maxdim = Inf, vdim = 1 ) RMgenfbm <- function(alpha, beta, var, scale, Aniso, proj) { cl <- match.call() submodels <- par.general <- par.model <- list() if (hasArg('alpha') && !is.null(subst <- substitute(alpha))) par.model[['alpha']] <- CheckArg(alpha, subst, TRUE) if (hasArg('beta') && !is.null(subst <- substitute(beta))) par.model[['beta']] <- CheckArg(beta, subst, TRUE) if (hasArg('var') && !is.null(subst <- substitute(var))) par.general[['var']] <- CheckArg(var, subst, TRUE) if (hasArg('scale') && !is.null(subst <- substitute(scale))) par.general[['scale']] <- CheckArg(scale, subst, TRUE) if (hasArg('Aniso') && !is.null(subst <- substitute(Aniso))) par.general[['Aniso']] <- CheckArg(Aniso, subst, TRUE) if (hasArg('proj') && !is.null(subst <- substitute(proj))) par.general[['proj']] <- CheckMixed(proj, subst, PROJECTION_NAMES) model <- methods::new('RMmodel', call = cl, name = 'RMgenfbm', submodels = submodels, par.model = par.model, par.general = par.general) return(model) } RMgenfbm <- new(CLASS_RM, .Data = RMgenfbm, type = c('variogram'), isotropy = c('isotropic'), domain = c('single variable'), operator = FALSE, monotone = 'monotone', finiterange = FALSE, simpleArguments = TRUE, maxdim = Inf, vdim = 1 ) RMgencauchy <- function(alpha, beta, var, scale, Aniso, proj) { cl <- match.call() submodels <- par.general <- par.model <- list() if (hasArg('alpha') && !is.null(subst <- substitute(alpha))) par.model[['alpha']] <- CheckArg(alpha, subst, TRUE) if (hasArg('beta') && !is.null(subst <- substitute(beta))) par.model[['beta']] <- CheckArg(beta, subst, TRUE) if (hasArg('var') && !is.null(subst <- substitute(var))) par.general[['var']] <- CheckArg(var, subst, TRUE) if (hasArg('scale') && !is.null(subst <- substitute(scale))) par.general[['scale']] <- CheckArg(scale, subst, TRUE) if (hasArg('Aniso') && !is.null(subst <- substitute(Aniso))) par.general[['Aniso']] <- CheckArg(Aniso, subst, TRUE) if (hasArg('proj') && !is.null(subst <- substitute(proj))) par.general[['proj']] <- CheckMixed(proj, subst, PROJECTION_NAMES) model <- methods::new('RMmodel', call = cl, name = 'RMgencauchy', submodels = submodels, par.model = par.model, par.general = par.general) return(model) } RMgencauchy <- new(CLASS_RM, .Data = RMgencauchy, type = c('positive definite', 'tail correlation', 'positive definite'), isotropy = c('isotropic', 'isotropic', 'spherical isotropic'), domain = c('single variable'), operator = FALSE, monotone = 'parameter dependent monotonicity', finiterange = FALSE, simpleArguments = TRUE, maxdim = Inf, vdim = 1 ) RMbicauchy <- function(alpha, beta, s, rho, var, scale, Aniso, proj) { cl <- match.call() submodels <- par.general <- par.model <- list() if (hasArg('alpha') && !is.null(subst <- substitute(alpha))) par.model[['alpha']] <- CheckArg(alpha, subst, TRUE) if (hasArg('beta') && !is.null(subst <- substitute(beta))) par.model[['beta']] <- CheckArg(beta, subst, TRUE) if (hasArg('s') && !is.null(subst <- substitute(s))) par.model[['s']] <- CheckArg(s, subst, TRUE) if (hasArg('rho') && !is.null(subst <- substitute(rho))) par.model[['rho']] <- CheckArg(rho, subst, TRUE) if (hasArg('var') && !is.null(subst <- substitute(var))) par.general[['var']] <- CheckArg(var, subst, TRUE) if (hasArg('scale') && !is.null(subst <- substitute(scale))) par.general[['scale']] <- CheckArg(scale, subst, TRUE) if (hasArg('Aniso') && !is.null(subst <- substitute(Aniso))) par.general[['Aniso']] <- CheckArg(Aniso, subst, TRUE) if (hasArg('proj') && !is.null(subst <- substitute(proj))) par.general[['proj']] <- CheckMixed(proj, subst, PROJECTION_NAMES) model <- methods::new('RMmodel', call = cl, name = 'RMbicauchy', submodels = submodels, par.model = par.model, par.general = par.general) return(model) } RMbicauchy <- new(CLASS_RM, .Data = RMbicauchy, type = c('positive definite'), isotropy = c('isotropic'), domain = c('single variable'), operator = FALSE, monotone = 'monotone', finiterange = FALSE, simpleArguments = TRUE, maxdim = 3, vdim = 2 ) RMgengneiting <- function(kappa, mu, var, scale, Aniso, proj) { cl <- match.call() submodels <- par.general <- par.model <- list() if (hasArg('kappa') && !is.null(subst <- substitute(kappa))) par.model[['kappa']] <- CheckArg(kappa, subst, TRUE) if (hasArg('mu') && !is.null(subst <- substitute(mu))) par.model[['mu']] <- CheckArg(mu, subst, TRUE) if (hasArg('var') && !is.null(subst <- substitute(var))) par.general[['var']] <- CheckArg(var, subst, TRUE) if (hasArg('scale') && !is.null(subst <- substitute(scale))) par.general[['scale']] <- CheckArg(scale, subst, TRUE) if (hasArg('Aniso') && !is.null(subst <- substitute(Aniso))) par.general[['Aniso']] <- CheckArg(Aniso, subst, TRUE) if (hasArg('proj') && !is.null(subst <- substitute(proj))) par.general[['proj']] <- CheckMixed(proj, subst, PROJECTION_NAMES) model <- methods::new('RMmodel', call = cl, name = 'RMgengneiting', submodels = submodels, par.model = par.model, par.general = par.general) return(model) } RMgengneiting <- new(CLASS_RM, .Data = RMgengneiting, type = c('positive definite', 'positive definite', 'positive definite', 'positive definite', 'positive definite', 'positive definite'), isotropy = c('isotropic', 'spherical isotropic', 'isotropic', 'spherical isotropic', 'isotropic', 'spherical isotropic'), domain = c('single variable'), operator = FALSE, monotone = 'monotone', finiterange = TRUE, simpleArguments = TRUE, maxdim = Inf, vdim = 1 ) RMgneiting <- function(orig, var, scale, Aniso, proj) { cl <- match.call() submodels <- par.general <- par.model <- list() if (hasArg('orig') && !is.null(subst <- substitute(orig))) par.model[['orig']] <- CheckArg(orig, subst, TRUE) if (hasArg('var') && !is.null(subst <- substitute(var))) par.general[['var']] <- CheckArg(var, subst, TRUE) if (hasArg('scale') && !is.null(subst <- substitute(scale))) par.general[['scale']] <- CheckArg(scale, subst, TRUE) if (hasArg('Aniso') && !is.null(subst <- substitute(Aniso))) par.general[['Aniso']] <- CheckArg(Aniso, subst, TRUE) if (hasArg('proj') && !is.null(subst <- substitute(proj))) par.general[['proj']] <- CheckMixed(proj, subst, PROJECTION_NAMES) model <- methods::new('RMmodel', call = cl, name = 'RMgneiting', submodels = submodels, par.model = par.model, par.general = par.general) return(model) } RMgneiting <- new(CLASS_RM, .Data = RMgneiting, type = c('positive definite', 'positive definite'), isotropy = c('isotropic', 'spherical isotropic'), domain = c('single variable'), operator = FALSE, monotone = 'monotone', finiterange = TRUE, simpleArguments = TRUE, maxdim = -1, vdim = 1 ) RMgennsst <- function(phi, psi, dim_u, var, scale, Aniso, proj) { cl <- match.call() submodels <- par.general <- par.model <- list() if (hasArg(phi)) submodels[['phi']] <- phi if (hasArg(psi)) submodels[['psi']] <- psi if (hasArg('dim_u') && !is.null(subst <- substitute(dim_u))) par.model[['dim_u']] <- CheckArg(dim_u, subst, TRUE) if (hasArg('var') && !is.null(subst <- substitute(var))) par.general[['var']] <- CheckArg(var, subst, TRUE) if (hasArg('scale') && !is.null(subst <- substitute(scale))) par.general[['scale']] <- CheckArg(scale, subst, TRUE) if (hasArg('Aniso') && !is.null(subst <- substitute(Aniso))) par.general[['Aniso']] <- CheckArg(Aniso, subst, TRUE) if (hasArg('proj') && !is.null(subst <- substitute(proj))) par.general[['proj']] <- CheckMixed(proj, subst, PROJECTION_NAMES) model <- methods::new('RMmodel', call = cl, name = 'RMgennsst', submodels = submodels, par.model = par.model, par.general = par.general) return(model) } RMgennsst <- new(CLASS_RM, .Data = RMgennsst, type = c('positive definite', 'positive definite'), isotropy = c('symmetric', 'symmetric'), domain = c('submodel dependent'), operator = TRUE, monotone = 'not monotone', finiterange = FALSE, simpleArguments = TRUE, maxdim = -3, vdim = 1 ) RMhyperbolic <- function(nu, lambda, delta, var, scale, Aniso, proj) { cl <- match.call() submodels <- par.general <- par.model <- list() if (hasArg('nu') && !is.null(subst <- substitute(nu))) par.model[['nu']] <- CheckArg(nu, subst, TRUE) if (hasArg('lambda') && !is.null(subst <- substitute(lambda))) par.model[['lambda']] <- CheckArg(lambda, subst, TRUE) if (hasArg('delta') && !is.null(subst <- substitute(delta))) par.model[['delta']] <- CheckArg(delta, subst, TRUE) if (hasArg('var') && !is.null(subst <- substitute(var))) par.general[['var']] <- CheckArg(var, subst, TRUE) if (hasArg('scale') && !is.null(subst <- substitute(scale))) par.general[['scale']] <- CheckArg(scale, subst, TRUE) if (hasArg('Aniso') && !is.null(subst <- substitute(Aniso))) par.general[['Aniso']] <- CheckArg(Aniso, subst, TRUE) if (hasArg('proj') && !is.null(subst <- substitute(proj))) par.general[['proj']] <- CheckMixed(proj, subst, PROJECTION_NAMES) model <- methods::new('RMmodel', call = cl, name = 'RMhyperbolic', submodels = submodels, par.model = par.model, par.general = par.general) return(model) } RMhyperbolic <- new(CLASS_RM, .Data = RMhyperbolic, type = c('positive definite'), isotropy = c('isotropic'), domain = c('single variable'), operator = FALSE, monotone = 'normal mixture', finiterange = FALSE, simpleArguments = TRUE, maxdim = Inf, vdim = 1 ) RMiaco <- function(nu, lambda, delta, var, scale, Aniso, proj) { cl <- match.call() submodels <- par.general <- par.model <- list() if (hasArg('nu') && !is.null(subst <- substitute(nu))) par.model[['nu']] <- CheckArg(nu, subst, TRUE) if (hasArg('lambda') && !is.null(subst <- substitute(lambda))) par.model[['lambda']] <- CheckArg(lambda, subst, TRUE) if (hasArg('delta') && !is.null(subst <- substitute(delta))) par.model[['delta']] <- CheckArg(delta, subst, TRUE) if (hasArg('var') && !is.null(subst <- substitute(var))) par.general[['var']] <- CheckArg(var, subst, TRUE) if (hasArg('scale') && !is.null(subst <- substitute(scale))) par.general[['scale']] <- CheckArg(scale, subst, TRUE) if (hasArg('Aniso') && !is.null(subst <- substitute(Aniso))) par.general[['Aniso']] <- CheckArg(Aniso, subst, TRUE) if (hasArg('proj') && !is.null(subst <- substitute(proj))) par.general[['proj']] <- CheckMixed(proj, subst, PROJECTION_NAMES) model <- methods::new('RMmodel', call = cl, name = 'RMiaco', submodels = submodels, par.model = par.model, par.general = par.general) return(model) } RMiaco <- new(CLASS_RM, .Data = RMiaco, type = c('positive definite'), isotropy = c('space-isotropic'), domain = c('single variable'), operator = FALSE, monotone = 'not monotone', finiterange = FALSE, simpleArguments = TRUE, maxdim = Inf, vdim = 1 ) RMidmodel <- function(phi, vdim, var, scale, Aniso, proj) { cl <- match.call() submodels <- par.general <- par.model <- list() if (hasArg(phi)) submodels[['phi']] <- phi if (hasArg('vdim') && !is.null(subst <- substitute(vdim))) par.model[['vdim']] <- CheckArg(vdim, subst, TRUE) if (hasArg('var') && !is.null(subst <- substitute(var))) par.general[['var']] <- CheckArg(var, subst, TRUE) if (hasArg('scale') && !is.null(subst <- substitute(scale))) par.general[['scale']] <- CheckArg(scale, subst, TRUE) if (hasArg('Aniso') && !is.null(subst <- substitute(Aniso))) par.general[['Aniso']] <- CheckArg(Aniso, subst, TRUE) if (hasArg('proj') && !is.null(subst <- substitute(proj))) par.general[['proj']] <- CheckMixed(proj, subst, PROJECTION_NAMES) model <- methods::new('RMmodel', call = cl, name = 'RMidmodel', submodels = submodels, par.model = par.model, par.general = par.general) return(model) } RMidmodel <- new(CLASS_RM, .Data = RMidmodel, type = c('of manifold type'), isotropy = c('framework dependent'), domain = c('single variable', 'kernel'), operator = TRUE, monotone = 'submodel dependent monotonicity', finiterange = NA, simpleArguments = TRUE, maxdim = -3, vdim = -3 ) RMkolmogorov <- function(var, scale, Aniso, proj) { cl <- match.call() submodels <- par.general <- par.model <- list() if (hasArg('var') && !is.null(subst <- substitute(var))) par.general[['var']] <- CheckArg(var, subst, TRUE) if (hasArg('scale') && !is.null(subst <- substitute(scale))) par.general[['scale']] <- CheckArg(scale, subst, TRUE) if (hasArg('Aniso') && !is.null(subst <- substitute(Aniso))) par.general[['Aniso']] <- CheckArg(Aniso, subst, TRUE) if (hasArg('proj') && !is.null(subst <- substitute(proj))) par.general[['proj']] <- CheckMixed(proj, subst, PROJECTION_NAMES) model <- methods::new('RMmodel', call = cl, name = 'RMkolmogorov', submodels = submodels, par.model = par.model, par.general = par.general) return(model) } RMkolmogorov <- new(CLASS_RM, .Data = RMkolmogorov, type = c('variogram'), isotropy = c('vector-isotropic'), domain = c('single variable'), operator = FALSE, monotone = 'not monotone', finiterange = FALSE, simpleArguments = TRUE, maxdim = 3, vdim = 3 ) RMlgd <- function(alpha, beta, var, scale, Aniso, proj) { cl <- match.call() submodels <- par.general <- par.model <- list() if (hasArg('alpha') && !is.null(subst <- substitute(alpha))) par.model[['alpha']] <- CheckArg(alpha, subst, TRUE) if (hasArg('beta') && !is.null(subst <- substitute(beta))) par.model[['beta']] <- CheckArg(beta, subst, TRUE) if (hasArg('var') && !is.null(subst <- substitute(var))) par.general[['var']] <- CheckArg(var, subst, TRUE) if (hasArg('scale') && !is.null(subst <- substitute(scale))) par.general[['scale']] <- CheckArg(scale, subst, TRUE) if (hasArg('Aniso') && !is.null(subst <- substitute(Aniso))) par.general[['Aniso']] <- CheckArg(Aniso, subst, TRUE) if (hasArg('proj') && !is.null(subst <- substitute(proj))) par.general[['proj']] <- CheckMixed(proj, subst, PROJECTION_NAMES) model <- methods::new('RMmodel', call = cl, name = 'RMlgd', submodels = submodels, par.model = par.model, par.general = par.general) return(model) } RMlgd <- new(CLASS_RM, .Data = RMlgd, type = c('positive definite'), isotropy = c('isotropic'), domain = c('single variable'), operator = FALSE, monotone = 'monotone', finiterange = FALSE, simpleArguments = TRUE, maxdim = -1, vdim = 1 ) RMmastein <- function(phi, nu, delta, var, scale, Aniso, proj) { cl <- match.call() submodels <- par.general <- par.model <- list() if (hasArg(phi)) submodels[['phi']] <- phi if (hasArg('nu') && !is.null(subst <- substitute(nu))) par.model[['nu']] <- CheckArg(nu, subst, TRUE) if (hasArg('delta') && !is.null(subst <- substitute(delta))) par.model[['delta']] <- CheckArg(delta, subst, TRUE) if (hasArg('var') && !is.null(subst <- substitute(var))) par.general[['var']] <- CheckArg(var, subst, TRUE) if (hasArg('scale') && !is.null(subst <- substitute(scale))) par.general[['scale']] <- CheckArg(scale, subst, TRUE) if (hasArg('Aniso') && !is.null(subst <- substitute(Aniso))) par.general[['Aniso']] <- CheckArg(Aniso, subst, TRUE) if (hasArg('proj') && !is.null(subst <- substitute(proj))) par.general[['proj']] <- CheckMixed(proj, subst, PROJECTION_NAMES) model <- methods::new('RMmodel', call = cl, name = 'RMmastein', submodels = submodels, par.model = par.model, par.general = par.general) return(model) } RMmastein <- new(CLASS_RM, .Data = RMmastein, type = c('positive definite'), isotropy = c('space-isotropic'), domain = c('single variable'), operator = TRUE, monotone = 'not monotone', finiterange = FALSE, simpleArguments = TRUE, maxdim = -3, vdim = 1 ) RMma <- function(phi, alpha, theta, var, scale, Aniso, proj) { cl <- match.call() submodels <- par.general <- par.model <- list() if (hasArg(phi)) submodels[['phi']] <- phi if (hasArg('alpha') && !is.null(subst <- substitute(alpha))) par.model[['alpha']] <- CheckArg(alpha, subst, TRUE) if (hasArg('theta') && !is.null(subst <- substitute(theta))) par.model[['theta']] <- CheckArg(theta, subst, TRUE) if (hasArg('var') && !is.null(subst <- substitute(var))) par.general[['var']] <- CheckArg(var, subst, TRUE) if (hasArg('scale') && !is.null(subst <- substitute(scale))) par.general[['scale']] <- CheckArg(scale, subst, TRUE) if (hasArg('Aniso') && !is.null(subst <- substitute(Aniso))) par.general[['Aniso']] <- CheckArg(Aniso, subst, TRUE) if (hasArg('proj') && !is.null(subst <- substitute(proj))) par.general[['proj']] <- CheckMixed(proj, subst, PROJECTION_NAMES) model <- methods::new('RMmodel', call = cl, name = 'RMma', submodels = submodels, par.model = par.model, par.general = par.general) return(model) } RMma <- new(CLASS_RM, .Data = RMma, type = c('positive definite'), isotropy = c('symmetric'), domain = c('single variable'), operator = TRUE, monotone = 'not monotone', finiterange = FALSE, simpleArguments = TRUE, maxdim = -3, vdim = 1 ) RMintexp <- function(phi, var, scale, Aniso, proj) { cl <- match.call() submodels <- par.general <- par.model <- list() if (hasArg(phi)) submodels[['phi']] <- phi if (hasArg('var') && !is.null(subst <- substitute(var))) par.general[['var']] <- CheckArg(var, subst, TRUE) if (hasArg('scale') && !is.null(subst <- substitute(scale))) par.general[['scale']] <- CheckArg(scale, subst, TRUE) if (hasArg('Aniso') && !is.null(subst <- substitute(Aniso))) par.general[['Aniso']] <- CheckArg(Aniso, subst, TRUE) if (hasArg('proj') && !is.null(subst <- substitute(proj))) par.general[['proj']] <- CheckMixed(proj, subst, PROJECTION_NAMES) model <- methods::new('RMmodel', call = cl, name = 'RMintexp', submodels = submodels, par.model = par.model, par.general = par.general) return(model) } RMintexp <- new(CLASS_RM, .Data = RMintexp, type = c('positive definite'), isotropy = c('symmetric'), domain = c('single variable'), operator = TRUE, monotone = 'not monotone', finiterange = FALSE, simpleArguments = TRUE, maxdim = -3, vdim = 1 ) RMmatrix <- function(C0, C1, C2, C3, C4, C5, C6, C7, C8, C9, M, vdim, var, scale, Aniso, proj) { cl <- match.call() submodels <- par.general <- par.model <- list() if (hasArg(C0)) submodels[['C0']] <- C0 if (hasArg(C1)) submodels[['C1']] <- C1 if (hasArg(C2)) submodels[['C2']] <- C2 if (hasArg(C3)) submodels[['C3']] <- C3 if (hasArg(C4)) submodels[['C4']] <- C4 if (hasArg(C5)) submodels[['C5']] <- C5 if (hasArg(C6)) submodels[['C6']] <- C6 if (hasArg(C7)) submodels[['C7']] <- C7 if (hasArg(C8)) submodels[['C8']] <- C8 if (hasArg(C9)) submodels[['C9']] <- C9 if (hasArg('M') && !is.null(subst <- substitute(M))) par.model[['M']] <- CheckArg(M, subst, TRUE) if (hasArg('vdim') && !is.null(subst <- substitute(vdim))) par.model[['vdim']] <- CheckArg(vdim, subst, TRUE) if (hasArg('var') && !is.null(subst <- substitute(var))) par.general[['var']] <- CheckArg(var, subst, TRUE) if (hasArg('scale') && !is.null(subst <- substitute(scale))) par.general[['scale']] <- CheckArg(scale, subst, TRUE) if (hasArg('Aniso') && !is.null(subst <- substitute(Aniso))) par.general[['Aniso']] <- CheckArg(Aniso, subst, TRUE) if (hasArg('proj') && !is.null(subst <- substitute(proj))) par.general[['proj']] <- CheckMixed(proj, subst, PROJECTION_NAMES) model <- methods::new('RMmodel', call = cl, name = 'RMmatrix', submodels = submodels, par.model = par.model, par.general = par.general) return(model) } RMmatrix <- new(CLASS_RM, .Data = RMmatrix, type = c('of manifold type'), isotropy = c('submodel dependent'), domain = c('submodel dependent'), operator = TRUE, monotone = 'not monotone', finiterange = NA, simpleArguments = TRUE, maxdim = -3, vdim = -1 ) RMmatern <- function(nu, notinvnu, var, scale, Aniso, proj) { cl <- match.call() submodels <- par.general <- par.model <- list() if (hasArg('nu') && !is.null(subst <- substitute(nu))) par.model[['nu']] <- CheckArg(nu, subst, TRUE) if (hasArg('notinvnu') && !is.null(subst <- substitute(notinvnu))) par.model[['notinvnu']] <- CheckArg(notinvnu, subst, TRUE) if (hasArg('var') && !is.null(subst <- substitute(var))) par.general[['var']] <- CheckArg(var, subst, TRUE) if (hasArg('scale') && !is.null(subst <- substitute(scale))) par.general[['scale']] <- CheckArg(scale, subst, TRUE) if (hasArg('Aniso') && !is.null(subst <- substitute(Aniso))) par.general[['Aniso']] <- CheckArg(Aniso, subst, TRUE) if (hasArg('proj') && !is.null(subst <- substitute(proj))) par.general[['proj']] <- CheckMixed(proj, subst, PROJECTION_NAMES) model <- methods::new('RMmodel', call = cl, name = 'RMmatern', submodels = submodels, par.model = par.model, par.general = par.general) return(model) } RMmatern <- new(CLASS_RM, .Data = RMmatern, type = c('positive definite'), isotropy = c('parameter dependent'), domain = c('parameter dependent'), operator = FALSE, monotone = 'submodel dependent monotonicity', finiterange = FALSE, simpleArguments = TRUE, maxdim = Inf, vdim = 1 ) RMmqam <- function(phi, C1, C2, C3, C4, C5, C6, C7, C8, C9, theta, var, scale, Aniso, proj) { cl <- match.call() submodels <- par.general <- par.model <- list() if (hasArg(phi)) submodels[['phi']] <- phi if (hasArg(C1)) submodels[['C1']] <- C1 if (hasArg(C2)) submodels[['C2']] <- C2 if (hasArg(C3)) submodels[['C3']] <- C3 if (hasArg(C4)) submodels[['C4']] <- C4 if (hasArg(C5)) submodels[['C5']] <- C5 if (hasArg(C6)) submodels[['C6']] <- C6 if (hasArg(C7)) submodels[['C7']] <- C7 if (hasArg(C8)) submodels[['C8']] <- C8 if (hasArg(C9)) submodels[['C9']] <- C9 if (hasArg('theta') && !is.null(subst <- substitute(theta))) par.model[['theta']] <- CheckArg(theta, subst, TRUE) if (hasArg('var') && !is.null(subst <- substitute(var))) par.general[['var']] <- CheckArg(var, subst, TRUE) if (hasArg('scale') && !is.null(subst <- substitute(scale))) par.general[['scale']] <- CheckArg(scale, subst, TRUE) if (hasArg('Aniso') && !is.null(subst <- substitute(Aniso))) par.general[['Aniso']] <- CheckArg(Aniso, subst, TRUE) if (hasArg('proj') && !is.null(subst <- substitute(proj))) par.general[['proj']] <- CheckMixed(proj, subst, PROJECTION_NAMES) model <- methods::new('RMmodel', call = cl, name = 'RMmqam', submodels = submodels, par.model = par.model, par.general = par.general) return(model) } RMmqam <- new(CLASS_RM, .Data = RMmqam, type = c('positive definite'), isotropy = c('symmetric'), domain = c('single variable'), operator = TRUE, monotone = 'not monotone', finiterange = FALSE, simpleArguments = TRUE, maxdim = -3, vdim = -1 ) RMmultiquad <- function(delta, tau, var, scale, Aniso, proj) { cl <- match.call() submodels <- par.general <- par.model <- list() if (hasArg('delta') && !is.null(subst <- substitute(delta))) par.model[['delta']] <- CheckArg(delta, subst, TRUE) if (hasArg('tau') && !is.null(subst <- substitute(tau))) par.model[['tau']] <- CheckArg(tau, subst, TRUE) if (hasArg('var') && !is.null(subst <- substitute(var))) par.general[['var']] <- CheckArg(var, subst, TRUE) if (hasArg('scale') && !is.null(subst <- substitute(scale))) par.general[['scale']] <- CheckArg(scale, subst, TRUE) if (hasArg('Aniso') && !is.null(subst <- substitute(Aniso))) par.general[['Aniso']] <- CheckArg(Aniso, subst, TRUE) if (hasArg('proj') && !is.null(subst <- substitute(proj))) par.general[['proj']] <- CheckMixed(proj, subst, PROJECTION_NAMES) model <- methods::new('RMmodel', call = cl, name = 'RMmultiquad', submodels = submodels, par.model = par.model, par.general = par.general) return(model) } RMmultiquad <- new(CLASS_RM, .Data = RMmultiquad, type = c('positive definite'), isotropy = c('spherical isotropic'), domain = c('single variable'), operator = FALSE, monotone = 'monotone', finiterange = FALSE, simpleArguments = TRUE, maxdim = 2, vdim = 1 ) RMnatsc <- function(phi, var, scale, Aniso, proj) { cl <- match.call() submodels <- par.general <- par.model <- list() if (hasArg(phi)) submodels[['phi']] <- phi if (hasArg('var') && !is.null(subst <- substitute(var))) par.general[['var']] <- CheckArg(var, subst, TRUE) if (hasArg('scale') && !is.null(subst <- substitute(scale))) par.general[['scale']] <- CheckArg(scale, subst, TRUE) if (hasArg('Aniso') && !is.null(subst <- substitute(Aniso))) par.general[['Aniso']] <- CheckArg(Aniso, subst, TRUE) if (hasArg('proj') && !is.null(subst <- substitute(proj))) par.general[['proj']] <- CheckMixed(proj, subst, PROJECTION_NAMES) model <- methods::new('RMmodel', call = cl, name = 'RMnatsc', submodels = submodels, par.model = par.model, par.general = par.general) return(model) } RMnatsc <- new(CLASS_RM, .Data = RMnatsc, type = c('positive definite', 'tail correlation'), isotropy = c('isotropic', 'isotropic'), domain = c('single variable'), operator = TRUE, monotone = 'submodel dependent monotonicity', finiterange = NA, simpleArguments = TRUE, maxdim = -3, vdim = 1 ) RMnsst <- function(phi, psi, delta, var, scale, Aniso, proj) { cl <- match.call() submodels <- par.general <- par.model <- list() if (hasArg(phi)) submodels[['phi']] <- phi if (hasArg(psi)) submodels[['psi']] <- psi if (hasArg('delta') && !is.null(subst <- substitute(delta))) par.model[['delta']] <- CheckArg(delta, subst, TRUE) if (hasArg('var') && !is.null(subst <- substitute(var))) par.general[['var']] <- CheckArg(var, subst, TRUE) if (hasArg('scale') && !is.null(subst <- substitute(scale))) par.general[['scale']] <- CheckArg(scale, subst, TRUE) if (hasArg('Aniso') && !is.null(subst <- substitute(Aniso))) par.general[['Aniso']] <- CheckArg(Aniso, subst, TRUE) if (hasArg('proj') && !is.null(subst <- substitute(proj))) par.general[['proj']] <- CheckMixed(proj, subst, PROJECTION_NAMES) model <- methods::new('RMmodel', call = cl, name = 'RMnsst', submodels = submodels, par.model = par.model, par.general = par.general) return(model) } RMnsst <- new(CLASS_RM, .Data = RMnsst, type = c('positive definite'), isotropy = c('space-isotropic'), domain = c('single variable'), operator = TRUE, monotone = 'not monotone', finiterange = FALSE, simpleArguments = TRUE, maxdim = -3, vdim = 1 ) RMparswm <- function(nudiag, var, scale, Aniso, proj) { cl <- match.call() submodels <- par.general <- par.model <- list() if (hasArg('nudiag') && !is.null(subst <- substitute(nudiag))) par.model[['nudiag']] <- CheckArg(nudiag, subst, TRUE) if (hasArg('var') && !is.null(subst <- substitute(var))) par.general[['var']] <- CheckArg(var, subst, TRUE) if (hasArg('scale') && !is.null(subst <- substitute(scale))) par.general[['scale']] <- CheckArg(scale, subst, TRUE) if (hasArg('Aniso') && !is.null(subst <- substitute(Aniso))) par.general[['Aniso']] <- CheckArg(Aniso, subst, TRUE) if (hasArg('proj') && !is.null(subst <- substitute(proj))) par.general[['proj']] <- CheckMixed(proj, subst, PROJECTION_NAMES) model <- methods::new('RMmodel', call = cl, name = 'RMparswm', submodels = submodels, par.model = par.model, par.general = par.general) return(model) } RMparswm <- new(CLASS_RM, .Data = RMparswm, type = c('positive definite'), isotropy = c('isotropic'), domain = c('single variable'), operator = FALSE, monotone = 'not monotone', finiterange = FALSE, simpleArguments = TRUE, maxdim = Inf, vdim = -1 ) RMpenta <- function(var, scale, Aniso, proj) { cl <- match.call() submodels <- par.general <- par.model <- list() if (hasArg('var') && !is.null(subst <- substitute(var))) par.general[['var']] <- CheckArg(var, subst, TRUE) if (hasArg('scale') && !is.null(subst <- substitute(scale))) par.general[['scale']] <- CheckArg(scale, subst, TRUE) if (hasArg('Aniso') && !is.null(subst <- substitute(Aniso))) par.general[['Aniso']] <- CheckArg(Aniso, subst, TRUE) if (hasArg('proj') && !is.null(subst <- substitute(proj))) par.general[['proj']] <- CheckMixed(proj, subst, PROJECTION_NAMES) model <- methods::new('RMmodel', call = cl, name = 'RMpenta', submodels = submodels, par.model = par.model, par.general = par.general) return(model) } RMpenta <- new(CLASS_RM, .Data = RMpenta, type = c('positive definite', 'positive definite'), isotropy = c('isotropic', 'spherical isotropic'), domain = c('single variable'), operator = FALSE, monotone = 'monotone', finiterange = TRUE, simpleArguments = TRUE, maxdim = 3, vdim = 1 ) RMaskey <- function(alpha, var, scale, Aniso, proj) { cl <- match.call() submodels <- par.general <- par.model <- list() if (hasArg('alpha') && !is.null(subst <- substitute(alpha))) par.model[['alpha']] <- CheckArg(alpha, subst, TRUE) if (hasArg('var') && !is.null(subst <- substitute(var))) par.general[['var']] <- CheckArg(var, subst, TRUE) if (hasArg('scale') && !is.null(subst <- substitute(scale))) par.general[['scale']] <- CheckArg(scale, subst, TRUE) if (hasArg('Aniso') && !is.null(subst <- substitute(Aniso))) par.general[['Aniso']] <- CheckArg(Aniso, subst, TRUE) if (hasArg('proj') && !is.null(subst <- substitute(proj))) par.general[['proj']] <- CheckMixed(proj, subst, PROJECTION_NAMES) model <- methods::new('RMmodel', call = cl, name = 'RMaskey', submodels = submodels, par.model = par.model, par.general = par.general) return(model) } RMaskey <- new(CLASS_RM, .Data = RMaskey, type = c('positive definite', 'positive definite', 'tail correlation'), isotropy = c('isotropic', 'spherical isotropic', 'isotropic'), domain = c('single variable'), operator = FALSE, monotone = 'monotone', finiterange = TRUE, simpleArguments = TRUE, maxdim = Inf, vdim = 1 ) RMpower <- function(phi, alpha, var, scale, Aniso, proj) { cl <- match.call() submodels <- par.general <- par.model <- list() if (hasArg(phi)) submodels[['phi']] <- phi if (hasArg('alpha') && !is.null(subst <- substitute(alpha))) par.model[['alpha']] <- CheckArg(alpha, subst, TRUE) if (hasArg('var') && !is.null(subst <- substitute(var))) par.general[['var']] <- CheckArg(var, subst, TRUE) if (hasArg('scale') && !is.null(subst <- substitute(scale))) par.general[['scale']] <- CheckArg(scale, subst, TRUE) if (hasArg('Aniso') && !is.null(subst <- substitute(Aniso))) par.general[['Aniso']] <- CheckArg(Aniso, subst, TRUE) if (hasArg('proj') && !is.null(subst <- substitute(proj))) par.general[['proj']] <- CheckMixed(proj, subst, PROJECTION_NAMES) model <- methods::new('RMmodel', call = cl, name = 'RMpower', submodels = submodels, par.model = par.model, par.general = par.general) return(model) } RMpower <- new(CLASS_RM, .Data = RMpower, type = c('shape function', 'negative definite', 'positive definite', 'tail correlation'), isotropy = c('submodel dependent', 'submodel dependent', 'submodel dependent', 'isotropic'), domain = c('single variable'), operator = TRUE, monotone = 'not monotone', finiterange = NA, simpleArguments = TRUE, maxdim = -3, vdim = 1 ) RMprod <- function(phi, var, scale, Aniso, proj) { cl <- match.call() submodels <- par.general <- par.model <- list() if (hasArg(phi)) submodels[['phi']] <- phi if (hasArg('var') && !is.null(subst <- substitute(var))) par.general[['var']] <- CheckArg(var, subst, TRUE) if (hasArg('scale') && !is.null(subst <- substitute(scale))) par.general[['scale']] <- CheckArg(scale, subst, TRUE) if (hasArg('Aniso') && !is.null(subst <- substitute(Aniso))) par.general[['Aniso']] <- CheckArg(Aniso, subst, TRUE) if (hasArg('proj') && !is.null(subst <- substitute(proj))) par.general[['proj']] <- CheckMixed(proj, subst, PROJECTION_NAMES) model <- methods::new('RMmodel', call = cl, name = 'RMprod', submodels = submodels, par.model = par.model, par.general = par.general) return(model) } RMprod <- new(CLASS_RM, .Data = RMprod, type = c('positive definite'), isotropy = c('non-dimension-reducing'), domain = c('kernel'), operator = TRUE, monotone = 'not monotone', finiterange = FALSE, simpleArguments = TRUE, maxdim = Inf, vdim = -3 ) RMqam <- function(phi, C1, C2, C3, C4, C5, C6, C7, C8, C9, theta, var, scale, Aniso, proj) { cl <- match.call() submodels <- par.general <- par.model <- list() if (hasArg(phi)) submodels[['phi']] <- phi if (hasArg(C1)) submodels[['C1']] <- C1 if (hasArg(C2)) submodels[['C2']] <- C2 if (hasArg(C3)) submodels[['C3']] <- C3 if (hasArg(C4)) submodels[['C4']] <- C4 if (hasArg(C5)) submodels[['C5']] <- C5 if (hasArg(C6)) submodels[['C6']] <- C6 if (hasArg(C7)) submodels[['C7']] <- C7 if (hasArg(C8)) submodels[['C8']] <- C8 if (hasArg(C9)) submodels[['C9']] <- C9 if (hasArg('theta') && !is.null(subst <- substitute(theta))) par.model[['theta']] <- CheckArg(theta, subst, TRUE) if (hasArg('var') && !is.null(subst <- substitute(var))) par.general[['var']] <- CheckArg(var, subst, TRUE) if (hasArg('scale') && !is.null(subst <- substitute(scale))) par.general[['scale']] <- CheckArg(scale, subst, TRUE) if (hasArg('Aniso') && !is.null(subst <- substitute(Aniso))) par.general[['Aniso']] <- CheckArg(Aniso, subst, TRUE) if (hasArg('proj') && !is.null(subst <- substitute(proj))) par.general[['proj']] <- CheckMixed(proj, subst, PROJECTION_NAMES) model <- methods::new('RMmodel', call = cl, name = 'RMqam', submodels = submodels, par.model = par.model, par.general = par.general) return(model) } RMqam <- new(CLASS_RM, .Data = RMqam, type = c('positive definite'), isotropy = c('isotropic'), domain = c('single variable'), operator = TRUE, monotone = 'not monotone', finiterange = FALSE, simpleArguments = TRUE, maxdim = -3, vdim = 1 ) RMqexp <- function(alpha, var, scale, Aniso, proj) { cl <- match.call() submodels <- par.general <- par.model <- list() if (hasArg('alpha') && !is.null(subst <- substitute(alpha))) par.model[['alpha']] <- CheckArg(alpha, subst, TRUE) if (hasArg('var') && !is.null(subst <- substitute(var))) par.general[['var']] <- CheckArg(var, subst, TRUE) if (hasArg('scale') && !is.null(subst <- substitute(scale))) par.general[['scale']] <- CheckArg(scale, subst, TRUE) if (hasArg('Aniso') && !is.null(subst <- substitute(Aniso))) par.general[['Aniso']] <- CheckArg(Aniso, subst, TRUE) if (hasArg('proj') && !is.null(subst <- substitute(proj))) par.general[['proj']] <- CheckMixed(proj, subst, PROJECTION_NAMES) model <- methods::new('RMmodel', call = cl, name = 'RMqexp', submodels = submodels, par.model = par.model, par.general = par.general) return(model) } RMqexp <- new(CLASS_RM, .Data = RMqexp, type = c('positive definite'), isotropy = c('isotropic'), domain = c('single variable'), operator = FALSE, monotone = 'not monotone', finiterange = FALSE, simpleArguments = TRUE, maxdim = Inf, vdim = 1 ) RMscale <- function(phi, scaling, penalty, var, scale, Aniso, proj) { cl <- match.call() submodels <- par.general <- par.model <- list() if (hasArg(phi)) submodels[['phi']] <- phi if (hasArg(scaling)) submodels[['scaling']] <- scaling if (hasArg(penalty)) submodels[['penalty']] <- penalty if (hasArg('var') && !is.null(subst <- substitute(var))) par.general[['var']] <- CheckArg(var, subst, TRUE) if (hasArg('scale') && !is.null(subst <- substitute(scale))) par.general[['scale']] <- CheckArg(scale, subst, TRUE) if (hasArg('Aniso') && !is.null(subst <- substitute(Aniso))) par.general[['Aniso']] <- CheckArg(Aniso, subst, TRUE) if (hasArg('proj') && !is.null(subst <- substitute(proj))) par.general[['proj']] <- CheckMixed(proj, subst, PROJECTION_NAMES) model <- methods::new('RMmodel', call = cl, name = 'RMscale', submodels = submodels, par.model = par.model, par.general = par.general) return(model) } RMscale <- new(CLASS_RM, .Data = RMscale, type = c('positive definite'), isotropy = c('symmetric'), domain = c('kernel'), operator = TRUE, monotone = 'not monotone', finiterange = FALSE, simpleArguments = TRUE, maxdim = Inf, vdim = 1 ) RMschur <- function(phi, M, diag, rhored, var, scale, Aniso, proj) { cl <- match.call() submodels <- par.general <- par.model <- list() if (hasArg(phi)) submodels[['phi']] <- phi if (hasArg('M') && !is.null(subst <- substitute(M))) par.model[['M']] <- CheckArg(M, subst, TRUE) if (hasArg('diag') && !is.null(subst <- substitute(diag))) par.model[['diag']] <- CheckArg(diag, subst, TRUE) if (hasArg('rhored') && !is.null(subst <- substitute(rhored))) par.model[['rhored']] <- CheckArg(rhored, subst, TRUE) if (hasArg('var') && !is.null(subst <- substitute(var))) par.general[['var']] <- CheckArg(var, subst, TRUE) if (hasArg('scale') && !is.null(subst <- substitute(scale))) par.general[['scale']] <- CheckArg(scale, subst, TRUE) if (hasArg('Aniso') && !is.null(subst <- substitute(Aniso))) par.general[['Aniso']] <- CheckArg(Aniso, subst, TRUE) if (hasArg('proj') && !is.null(subst <- substitute(proj))) par.general[['proj']] <- CheckMixed(proj, subst, PROJECTION_NAMES) model <- methods::new('RMmodel', call = cl, name = 'RMschur', submodels = submodels, par.model = par.model, par.general = par.general) return(model) } RMschur <- new(CLASS_RM, .Data = RMschur, type = c('positive definite'), isotropy = c('framework dependent'), domain = c('single variable', 'kernel'), operator = TRUE, monotone = 'not monotone', finiterange = NA, simpleArguments = TRUE, maxdim = -3, vdim = -3 ) RMdelay <- function(phi, s, var, scale, Aniso, proj) { cl <- match.call() submodels <- par.general <- par.model <- list() if (hasArg(phi)) submodels[['phi']] <- phi if (hasArg('s') && !is.null(subst <- substitute(s))) par.model[['s']] <- CheckArg(s, subst, TRUE) if (hasArg('var') && !is.null(subst <- substitute(var))) par.general[['var']] <- CheckArg(var, subst, TRUE) if (hasArg('scale') && !is.null(subst <- substitute(scale))) par.general[['scale']] <- CheckArg(scale, subst, TRUE) if (hasArg('Aniso') && !is.null(subst <- substitute(Aniso))) par.general[['Aniso']] <- CheckArg(Aniso, subst, TRUE) if (hasArg('proj') && !is.null(subst <- substitute(proj))) par.general[['proj']] <- CheckMixed(proj, subst, PROJECTION_NAMES) model <- methods::new('RMmodel', call = cl, name = 'RMdelay', submodels = submodels, par.model = par.model, par.general = par.general) return(model) } RMdelay <- new(CLASS_RM, .Data = RMdelay, type = c('positive definite'), isotropy = c('cartesian system'), domain = c('single variable'), operator = TRUE, monotone = 'not monotone', finiterange = NA, simpleArguments = TRUE, maxdim = -3, vdim = -1 ) RMsinepower <- function(alpha, var, scale, Aniso, proj) { cl <- match.call() submodels <- par.general <- par.model <- list() if (hasArg('alpha') && !is.null(subst <- substitute(alpha))) par.model[['alpha']] <- CheckArg(alpha, subst, TRUE) if (hasArg('var') && !is.null(subst <- substitute(var))) par.general[['var']] <- CheckArg(var, subst, TRUE) if (hasArg('scale') && !is.null(subst <- substitute(scale))) par.general[['scale']] <- CheckArg(scale, subst, TRUE) if (hasArg('Aniso') && !is.null(subst <- substitute(Aniso))) par.general[['Aniso']] <- CheckArg(Aniso, subst, TRUE) if (hasArg('proj') && !is.null(subst <- substitute(proj))) par.general[['proj']] <- CheckMixed(proj, subst, PROJECTION_NAMES) model <- methods::new('RMmodel', call = cl, name = 'RMsinepower', submodels = submodels, par.model = par.model, par.general = par.general) return(model) } RMsinepower <- new(CLASS_RM, .Data = RMsinepower, type = c('positive definite'), isotropy = c('spherical isotropic'), domain = c('single variable'), operator = FALSE, monotone = 'monotone', finiterange = FALSE, simpleArguments = TRUE, maxdim = 2, vdim = 1 ) RMspheric <- function(var, scale, Aniso, proj) { cl <- match.call() submodels <- par.general <- par.model <- list() if (hasArg('var') && !is.null(subst <- substitute(var))) par.general[['var']] <- CheckArg(var, subst, TRUE) if (hasArg('scale') && !is.null(subst <- substitute(scale))) par.general[['scale']] <- CheckArg(scale, subst, TRUE) if (hasArg('Aniso') && !is.null(subst <- substitute(Aniso))) par.general[['Aniso']] <- CheckArg(Aniso, subst, TRUE) if (hasArg('proj') && !is.null(subst <- substitute(proj))) par.general[['proj']] <- CheckMixed(proj, subst, PROJECTION_NAMES) model <- methods::new('RMmodel', call = cl, name = 'RMspheric', submodels = submodels, par.model = par.model, par.general = par.general) return(model) } RMspheric <- new(CLASS_RM, .Data = RMspheric, type = c('tail correlation', 'positive definite'), isotropy = c('isotropic', 'spherical isotropic'), domain = c('single variable'), operator = FALSE, monotone = 'Gneiting-Schaback class', finiterange = TRUE, simpleArguments = TRUE, maxdim = 3, vdim = 1 ) RMstable <- function(alpha, var, scale, Aniso, proj) { cl <- match.call() submodels <- par.general <- par.model <- list() if (hasArg('alpha') && !is.null(subst <- substitute(alpha))) par.model[['alpha']] <- CheckArg(alpha, subst, TRUE) if (hasArg('var') && !is.null(subst <- substitute(var))) par.general[['var']] <- CheckArg(var, subst, TRUE) if (hasArg('scale') && !is.null(subst <- substitute(scale))) par.general[['scale']] <- CheckArg(scale, subst, TRUE) if (hasArg('Aniso') && !is.null(subst <- substitute(Aniso))) par.general[['Aniso']] <- CheckArg(Aniso, subst, TRUE) if (hasArg('proj') && !is.null(subst <- substitute(proj))) par.general[['proj']] <- CheckMixed(proj, subst, PROJECTION_NAMES) model <- methods::new('RMmodel', call = cl, name = 'RMstable', submodels = submodels, par.model = par.model, par.general = par.general) return(model) } RMstable <- new(CLASS_RM, .Data = RMstable, type = c('positive definite', 'tail correlation', 'positive definite'), isotropy = c('isotropic', 'isotropic', 'spherical isotropic'), domain = c('single variable'), operator = FALSE, monotone = 'parameter dependent monotonicity', finiterange = FALSE, simpleArguments = TRUE, maxdim = Inf, vdim = 1 ) RMintrinsic <- function(phi, diameter, rawR, var, scale, Aniso, proj) { cl <- match.call() submodels <- par.general <- par.model <- list() if (hasArg(phi)) submodels[['phi']] <- phi if (hasArg('diameter') && !is.null(subst <- substitute(diameter))) par.model[['diameter']] <- CheckArg(diameter, subst, TRUE) if (hasArg('rawR') && !is.null(subst <- substitute(rawR))) par.model[['rawR']] <- CheckArg(rawR, subst, TRUE) if (hasArg('var') && !is.null(subst <- substitute(var))) par.general[['var']] <- CheckArg(var, subst, TRUE) if (hasArg('scale') && !is.null(subst <- substitute(scale))) par.general[['scale']] <- CheckArg(scale, subst, TRUE) if (hasArg('Aniso') && !is.null(subst <- substitute(Aniso))) par.general[['Aniso']] <- CheckArg(Aniso, subst, TRUE) if (hasArg('proj') && !is.null(subst <- substitute(proj))) par.general[['proj']] <- CheckMixed(proj, subst, PROJECTION_NAMES) model <- methods::new('RMmodel', call = cl, name = 'RMintrinsic', submodels = submodels, par.model = par.model, par.general = par.general) return(model) } RMintrinsic <- new(CLASS_RM, .Data = RMintrinsic, type = c('positive definite', 'positive definite'), isotropy = c('isotropic', 'spherical isotropic'), domain = c('single variable'), operator = TRUE, monotone = 'not monotone', finiterange = TRUE, simpleArguments = TRUE, maxdim = 13, vdim = 1 ) RMstein <- function(nu, z, var, scale, Aniso, proj) { cl <- match.call() submodels <- par.general <- par.model <- list() if (hasArg('nu') && !is.null(subst <- substitute(nu))) par.model[['nu']] <- CheckArg(nu, subst, TRUE) if (hasArg('z') && !is.null(subst <- substitute(z))) par.model[['z']] <- CheckArg(z, subst, TRUE) if (hasArg('var') && !is.null(subst <- substitute(var))) par.general[['var']] <- CheckArg(var, subst, TRUE) if (hasArg('scale') && !is.null(subst <- substitute(scale))) par.general[['scale']] <- CheckArg(scale, subst, TRUE) if (hasArg('Aniso') && !is.null(subst <- substitute(Aniso))) par.general[['Aniso']] <- CheckArg(Aniso, subst, TRUE) if (hasArg('proj') && !is.null(subst <- substitute(proj))) par.general[['proj']] <- CheckMixed(proj, subst, PROJECTION_NAMES) model <- methods::new('RMmodel', call = cl, name = 'RMstein', submodels = submodels, par.model = par.model, par.general = par.general) return(model) } RMstein <- new(CLASS_RM, .Data = RMstein, type = c('positive definite'), isotropy = c('symmetric'), domain = c('single variable'), operator = FALSE, monotone = 'not monotone', finiterange = FALSE, simpleArguments = TRUE, maxdim = Inf, vdim = 1 ) RMstp <- function(xi, phi, S, z, M, var, scale, Aniso, proj) { cl <- match.call() submodels <- par.general <- par.model <- list() if (hasArg(xi)) submodels[['xi']] <- xi if (hasArg(phi)) submodels[['phi']] <- phi if (hasArg('S') && !is.null(subst <- substitute(S))) par.model[['S']] <- CheckArg(S, subst, TRUE) if (hasArg('z') && !is.null(subst <- substitute(z))) par.model[['z']] <- CheckArg(z, subst, TRUE) if (hasArg('M') && !is.null(subst <- substitute(M))) par.model[['M']] <- CheckArg(M, subst, TRUE) if (hasArg('var') && !is.null(subst <- substitute(var))) par.general[['var']] <- CheckArg(var, subst, TRUE) if (hasArg('scale') && !is.null(subst <- substitute(scale))) par.general[['scale']] <- CheckArg(scale, subst, TRUE) if (hasArg('Aniso') && !is.null(subst <- substitute(Aniso))) par.general[['Aniso']] <- CheckArg(Aniso, subst, TRUE) if (hasArg('proj') && !is.null(subst <- substitute(proj))) par.general[['proj']] <- CheckMixed(proj, subst, PROJECTION_NAMES) model <- methods::new('RMmodel', call = cl, name = 'RMstp', submodels = submodels, par.model = par.model, par.general = par.general) return(model) } RMstp <- new(CLASS_RM, .Data = RMstp, type = c('positive definite'), isotropy = c('symmetric'), domain = c('kernel'), operator = TRUE, monotone = 'not monotone', finiterange = FALSE, simpleArguments = TRUE, maxdim = 10, vdim = 1 ) RMtbm <- function(phi, fulldim, reduceddim, layers, var, scale, Aniso, proj) { cl <- match.call() submodels <- par.general <- par.model <- list() if (hasArg(phi)) submodels[['phi']] <- phi if (hasArg('fulldim') && !is.null(subst <- substitute(fulldim))) par.model[['fulldim']] <- CheckArg(fulldim, subst, TRUE) if (hasArg('reduceddim') && !is.null(subst <- substitute(reduceddim))) par.model[['reduceddim']] <- CheckArg(reduceddim, subst, TRUE) if (hasArg('layers') && !is.null(subst <- substitute(layers))) par.model[['layers']] <- CheckArg(layers, subst, TRUE) if (hasArg('var') && !is.null(subst <- substitute(var))) par.general[['var']] <- CheckArg(var, subst, TRUE) if (hasArg('scale') && !is.null(subst <- substitute(scale))) par.general[['scale']] <- CheckArg(scale, subst, TRUE) if (hasArg('Aniso') && !is.null(subst <- substitute(Aniso))) par.general[['Aniso']] <- CheckArg(Aniso, subst, TRUE) if (hasArg('proj') && !is.null(subst <- substitute(proj))) par.general[['proj']] <- CheckMixed(proj, subst, PROJECTION_NAMES) model <- methods::new('RMmodel', call = cl, name = 'RMtbm', submodels = submodels, par.model = par.model, par.general = par.general) return(model) } RMtbm <- new(CLASS_RM, .Data = RMtbm, type = c('of manifold type'), isotropy = c('parameter dependent'), domain = c('single variable'), operator = TRUE, monotone = 'not monotone', finiterange = NA, simpleArguments = TRUE, maxdim = -1, vdim = -3 ) RMsum <- function(phi, var, scale, Aniso, proj) { cl <- match.call() submodels <- par.general <- par.model <- list() if (hasArg(phi)) submodels[['phi']] <- phi if (hasArg('var') && !is.null(subst <- substitute(var))) par.general[['var']] <- CheckArg(var, subst, TRUE) if (hasArg('scale') && !is.null(subst <- substitute(scale))) par.general[['scale']] <- CheckArg(scale, subst, TRUE) if (hasArg('Aniso') && !is.null(subst <- substitute(Aniso))) par.general[['Aniso']] <- CheckArg(Aniso, subst, TRUE) if (hasArg('proj') && !is.null(subst <- substitute(proj))) par.general[['proj']] <- CheckMixed(proj, subst, PROJECTION_NAMES) model <- methods::new('RMmodel', call = cl, name = 'RMsum', submodels = submodels, par.model = par.model, par.general = par.general) return(model) } RMsum <- new(CLASS_RM, .Data = RMsum, type = c('negative definite'), isotropy = c('non-dimension-reducing'), domain = c('kernel'), operator = TRUE, monotone = 'not monotone', finiterange = FALSE, simpleArguments = TRUE, maxdim = Inf, vdim = -3 ) iRMcov <- function(gamma, x, a, var, scale, Aniso, proj) { cl <- match.call() submodels <- par.general <- par.model <- list() if (hasArg(gamma)) submodels[['gamma']] <- gamma if (hasArg('x') && !is.null(subst <- substitute(x))) par.model[['x']] <- CheckArg(x, subst, TRUE) if (hasArg('a') && !is.null(subst <- substitute(a))) par.model[['a']] <- CheckArg(a, subst, TRUE) if (hasArg('var') && !is.null(subst <- substitute(var))) par.general[['var']] <- CheckArg(var, subst, TRUE) if (hasArg('scale') && !is.null(subst <- substitute(scale))) par.general[['scale']] <- CheckArg(scale, subst, TRUE) if (hasArg('Aniso') && !is.null(subst <- substitute(Aniso))) par.general[['Aniso']] <- CheckArg(Aniso, subst, TRUE) if (hasArg('proj') && !is.null(subst <- substitute(proj))) par.general[['proj']] <- CheckMixed(proj, subst, PROJECTION_NAMES) model <- methods::new('RMmodel', call = cl, name = 'RMcov', submodels = submodels, par.model = par.model, par.general = par.general) return(model) } iRMcov <- new(CLASS_RM, .Data = iRMcov, type = c('positive definite'), isotropy = c('cartesian system'), domain = c('kernel'), operator = TRUE, monotone = 'not monotone', finiterange = FALSE, simpleArguments = FALSE, maxdim = Inf, vdim = 1 ) RMvector <- function(phi, a, Dspace, var, scale, Aniso, proj) { cl <- match.call() submodels <- par.general <- par.model <- list() if (hasArg(phi)) submodels[['phi']] <- phi if (hasArg('a') && !is.null(subst <- substitute(a))) par.model[['a']] <- CheckArg(a, subst, TRUE) if (hasArg('Dspace') && !is.null(subst <- substitute(Dspace))) par.model[['Dspace']] <- CheckArg(Dspace, subst, TRUE) if (hasArg('var') && !is.null(subst <- substitute(var))) par.general[['var']] <- CheckArg(var, subst, TRUE) if (hasArg('scale') && !is.null(subst <- substitute(scale))) par.general[['scale']] <- CheckArg(scale, subst, TRUE) if (hasArg('Aniso') && !is.null(subst <- substitute(Aniso))) par.general[['Aniso']] <- CheckArg(Aniso, subst, TRUE) if (hasArg('proj') && !is.null(subst <- substitute(proj))) par.general[['proj']] <- CheckMixed(proj, subst, PROJECTION_NAMES) model <- methods::new('RMmodel', call = cl, name = 'RMvector', submodels = submodels, par.model = par.model, par.general = par.general) return(model) } RMvector <- new(CLASS_RM, .Data = RMvector, type = c('positive definite', 'positive definite'), isotropy = c('cartesian system', 'cartesian system'), domain = c('single variable'), operator = TRUE, monotone = 'not monotone', finiterange = NA, simpleArguments = TRUE, maxdim = -3, vdim = -1 ) RMwave <- function(var, scale, Aniso, proj) { cl <- match.call() submodels <- par.general <- par.model <- list() if (hasArg('var') && !is.null(subst <- substitute(var))) par.general[['var']] <- CheckArg(var, subst, TRUE) if (hasArg('scale') && !is.null(subst <- substitute(scale))) par.general[['scale']] <- CheckArg(scale, subst, TRUE) if (hasArg('Aniso') && !is.null(subst <- substitute(Aniso))) par.general[['Aniso']] <- CheckArg(Aniso, subst, TRUE) if (hasArg('proj') && !is.null(subst <- substitute(proj))) par.general[['proj']] <- CheckMixed(proj, subst, PROJECTION_NAMES) model <- methods::new('RMmodel', call = cl, name = 'RMwave', submodels = submodels, par.model = par.model, par.general = par.general) return(model) } RMwave <- new(CLASS_RM, .Data = RMwave, type = c('positive definite'), isotropy = c('isotropic'), domain = c('single variable'), operator = FALSE, monotone = 'not monotone', finiterange = FALSE, simpleArguments = TRUE, maxdim = 3, vdim = 1 ) RMwhittle <- function(nu, notinvnu, var, scale, Aniso, proj) { cl <- match.call() submodels <- par.general <- par.model <- list() if (hasArg('nu') && !is.null(subst <- substitute(nu))) par.model[['nu']] <- CheckArg(nu, subst, TRUE) if (hasArg('notinvnu') && !is.null(subst <- substitute(notinvnu))) par.model[['notinvnu']] <- CheckArg(notinvnu, subst, TRUE) if (hasArg('var') && !is.null(subst <- substitute(var))) par.general[['var']] <- CheckArg(var, subst, TRUE) if (hasArg('scale') && !is.null(subst <- substitute(scale))) par.general[['scale']] <- CheckArg(scale, subst, TRUE) if (hasArg('Aniso') && !is.null(subst <- substitute(Aniso))) par.general[['Aniso']] <- CheckArg(Aniso, subst, TRUE) if (hasArg('proj') && !is.null(subst <- substitute(proj))) par.general[['proj']] <- CheckMixed(proj, subst, PROJECTION_NAMES) model <- methods::new('RMmodel', call = cl, name = 'RMwhittle', submodels = submodels, par.model = par.model, par.general = par.general) return(model) } RMwhittle <- new(CLASS_RM, .Data = RMwhittle, type = c('positive definite'), isotropy = c('parameter dependent'), domain = c('parameter dependent'), operator = FALSE, monotone = 'normal mixture', finiterange = FALSE, simpleArguments = TRUE, maxdim = Inf, vdim = 1 ) RMnugget <- function(tol, vdim, var, Aniso, proj) { cl <- match.call() submodels <- par.general <- par.model <- list() if (hasArg('tol') && !is.null(subst <- substitute(tol))) par.model[['tol']] <- CheckArg(tol, subst, TRUE) if (hasArg('vdim') && !is.null(subst <- substitute(vdim))) par.model[['vdim']] <- CheckArg(vdim, subst, TRUE) if (hasArg('var') && !is.null(subst <- substitute(var))) par.general[['var']] <- CheckArg(var, subst, TRUE) if (hasArg('Aniso') && !is.null(subst <- substitute(Aniso))) par.general[['Aniso']] <- CheckArg(Aniso, subst, TRUE) if (hasArg('proj') && !is.null(subst <- substitute(proj))) par.general[['proj']] <- CheckMixed(proj, subst, PROJECTION_NAMES) model <- methods::new('RMmodel', call = cl, name = 'RMnugget', submodels = submodels, par.model = par.model, par.general = par.general) return(model) } RMnugget <- new(CLASS_RM, .Data = RMnugget, type = c('tail correlation'), isotropy = c('parameter dependent'), domain = c('parameter dependent'), operator = FALSE, monotone = 'monotone', finiterange = TRUE, simpleArguments = TRUE, maxdim = Inf, vdim = -2 ) RMtrend <- function(mean) { cl <- match.call() submodels <- par.general <- par.model <- list() if (hasArg('mean') && !is.null(subst <- substitute(mean))) par.model[['mean']] <- CheckArg(mean, subst, FALSE) model <- methods::new('RMmodel', call = cl, name = 'RMtrend', submodels = submodels, par.model = par.model, par.general = par.general) return(model) } RMtrend <- new(CLASS_RM, .Data = RMtrend, type = c('trend'), isotropy = c('parameter dependent'), domain = c('single variable'), operator = FALSE, monotone = 'not monotone', finiterange = FALSE, simpleArguments = TRUE, maxdim = Inf, vdim = -1 ) RMangle <- function(angle, lat.angle, ratio, diag) { cl <- match.call() submodels <- par.general <- par.model <- list() if (hasArg('angle') && !is.null(subst <- substitute(angle))) par.model[['angle']] <- CheckArg(angle, subst, TRUE) if (hasArg('lat.angle') && !is.null(subst <- substitute(lat.angle))) par.model[['lat.angle']] <- CheckArg(lat.angle, subst, TRUE) if (hasArg('ratio') && !is.null(subst <- substitute(ratio))) par.model[['ratio']] <- CheckArg(ratio, subst, TRUE) if (hasArg('diag') && !is.null(subst <- substitute(diag))) par.model[['diag']] <- CheckArg(diag, subst, TRUE) model <- methods::new('RMmodel', call = cl, name = 'RMangle', submodels = submodels, par.model = par.model, par.general = par.general) return(model) } RMangle <- new(CLASS_RM, .Data = RMangle, type = c('shape function'), isotropy = c('cartesian system'), domain = c('single variable'), operator = FALSE, monotone = 'not monotone', finiterange = FALSE, simpleArguments = TRUE, maxdim = Inf, vdim = -1 ) RMball <- function(var, scale, Aniso, proj) { cl <- match.call() submodels <- par.general <- par.model <- list() if (hasArg('var') && !is.null(subst <- substitute(var))) par.general[['var']] <- CheckArg(var, subst, TRUE) if (hasArg('scale') && !is.null(subst <- substitute(scale))) par.general[['scale']] <- CheckArg(scale, subst, TRUE) if (hasArg('Aniso') && !is.null(subst <- substitute(Aniso))) par.general[['Aniso']] <- CheckArg(Aniso, subst, TRUE) if (hasArg('proj') && !is.null(subst <- substitute(proj))) par.general[['proj']] <- CheckMixed(proj, subst, PROJECTION_NAMES) model <- methods::new('RMmodel', call = cl, name = 'RMball', submodels = submodels, par.model = par.model, par.general = par.general) return(model) } RMball <- new(CLASS_RM, .Data = RMball, type = c('shape function'), isotropy = c('isotropic'), domain = c('single variable'), operator = FALSE, monotone = 'monotone', finiterange = TRUE, simpleArguments = TRUE, maxdim = Inf, vdim = 1 ) iRMcovariate <- function(norm, data, x, raw, addNA, factor, var) { cl <- match.call() submodels <- par.general <- par.model <- list() if (hasArg(norm)) submodels[['norm']] <- norm if (hasArg('data') && !is.null(subst <- substitute(data))) par.model[['data']] <- CheckArg(data, subst, TRUE) if (hasArg('x') && !is.null(subst <- substitute(x))) par.model[['x']] <- CheckArg(x, subst, TRUE) if (hasArg('raw') && !is.null(subst <- substitute(raw))) par.model[['raw']] <- CheckArg(raw, subst, TRUE) if (hasArg('addNA') && !is.null(subst <- substitute(addNA))) par.model[['addNA']] <- CheckArg(addNA, subst, TRUE) if (hasArg('factor') && !is.null(subst <- substitute(factor))) par.model[['factor']] <- CheckArg(factor, subst, TRUE) if (hasArg('var') && !is.null(subst <- substitute(var))) par.general[['var']] <- CheckArg(var, subst, TRUE) model <- methods::new('RMmodel', call = cl, name = 'RMcovariate', submodels = submodels, par.model = par.model, par.general = par.general) return(model) } iRMcovariate <- new(CLASS_RM, .Data = iRMcovariate, type = c('shape function', 'shape function', 'shape function', 'trend'), isotropy = c('non-dimension-reducing', 'isotropic', 'earth isotropic', 'non-dimension-reducing'), domain = c('single variable'), operator = TRUE, monotone = 'not monotone', finiterange = FALSE, simpleArguments = FALSE, maxdim = Inf, vdim = -1 ) RMeaxxa <- function(E, A) { cl <- match.call() submodels <- par.general <- par.model <- list() if (hasArg('E') && !is.null(subst <- substitute(E))) par.model[['E']] <- CheckArg(E, subst, TRUE) if (hasArg('A') && !is.null(subst <- substitute(A))) par.model[['A']] <- CheckArg(A, subst, TRUE) model <- methods::new('RMmodel', call = cl, name = 'RMeaxxa', submodels = submodels, par.model = par.model, par.general = par.general) return(model) } RMeaxxa <- new(CLASS_RM, .Data = RMeaxxa, type = c('shape function'), isotropy = c('cartesian system'), domain = c('single variable'), operator = FALSE, monotone = 'not monotone', finiterange = FALSE, simpleArguments = TRUE, maxdim = 10, vdim = -1 ) RMetaxxa <- function(E, A, alpha) { cl <- match.call() submodels <- par.general <- par.model <- list() if (hasArg('E') && !is.null(subst <- substitute(E))) par.model[['E']] <- CheckArg(E, subst, TRUE) if (hasArg('A') && !is.null(subst <- substitute(A))) par.model[['A']] <- CheckArg(A, subst, TRUE) if (hasArg('alpha') && !is.null(subst <- substitute(alpha))) par.model[['alpha']] <- CheckArg(alpha, subst, TRUE) model <- methods::new('RMmodel', call = cl, name = 'RMetaxxa', submodels = submodels, par.model = par.model, par.general = par.general) return(model) } RMetaxxa <- new(CLASS_RM, .Data = RMetaxxa, type = c('shape function'), isotropy = c('cartesian system'), domain = c('single variable'), operator = FALSE, monotone = 'not monotone', finiterange = FALSE, simpleArguments = TRUE, maxdim = 10, vdim = 3 ) RMid <- function() { cl <- match.call() submodels <- par.general <- par.model <- list() model <- methods::new('RMmodel', call = cl, name = 'RMid', submodels = submodels, par.model = par.model, par.general = par.general) return(model) } RMid <- new(CLASS_RM, .Data = RMid, type = c('shape function'), isotropy = c('framework dependent'), domain = c('single variable'), operator = FALSE, monotone = 'not monotone', finiterange = FALSE, simpleArguments = TRUE, maxdim = Inf, vdim = -1 ) RMtrafo <- function(phi, new) { cl <- match.call() submodels <- par.general <- par.model <- list() if (hasArg(phi)) submodels[['phi']] <- phi if (hasArg('new') && !is.null(subst <- substitute(new))) par.model[['new']] <- CheckChar(new, subst, ISO_NAMES, TRUE) model <- methods::new('RMmodel', call = cl, name = 'RMtrafo', submodels = submodels, par.model = par.model, par.general = par.general) return(model) } RMtrafo <- new(CLASS_RM, .Data = RMtrafo, type = c('of manifold type'), isotropy = c('parameter dependent'), domain = c('parameter dependent'), operator = TRUE, monotone = 'not monotone', finiterange = FALSE, simpleArguments = TRUE, maxdim = Inf, vdim = -1 ) RMpolygon <- function(lambda) { cl <- match.call() submodels <- par.general <- par.model <- list() if (hasArg('lambda') && !is.null(subst <- substitute(lambda))) par.model[['lambda']] <- CheckArg(lambda, subst, TRUE) model <- methods::new('RMmodel', call = cl, name = 'RMpolygon', submodels = submodels, par.model = par.model, par.general = par.general) return(model) } RMpolygon <- new(CLASS_RM, .Data = RMpolygon, type = c('shape function'), isotropy = c('cartesian system'), domain = c('single variable'), operator = FALSE, monotone = 'monotone', finiterange = TRUE, simpleArguments = TRUE, maxdim = 2, vdim = 1 ) RMrational <- function(A, a) { cl <- match.call() submodels <- par.general <- par.model <- list() if (hasArg('A') && !is.null(subst <- substitute(A))) par.model[['A']] <- CheckArg(A, subst, TRUE) if (hasArg('a') && !is.null(subst <- substitute(a))) par.model[['a']] <- CheckArg(a, subst, TRUE) model <- methods::new('RMmodel', call = cl, name = 'RMrational', submodels = submodels, par.model = par.model, par.general = par.general) return(model) } RMrational <- new(CLASS_RM, .Data = RMrational, type = c('shape function'), isotropy = c('cartesian system'), domain = c('single variable'), operator = FALSE, monotone = 'not monotone', finiterange = FALSE, simpleArguments = TRUE, maxdim = Inf, vdim = 1 ) RMrotat <- function(speed, phi) { cl <- match.call() submodels <- par.general <- par.model <- list() if (hasArg('speed') && !is.null(subst <- substitute(speed))) par.model[['speed']] <- CheckArg(speed, subst, TRUE) if (hasArg('phi') && !is.null(subst <- substitute(phi))) par.model[['phi']] <- CheckArg(phi, subst, TRUE) model <- methods::new('RMmodel', call = cl, name = 'RMrotat', submodels = submodels, par.model = par.model, par.general = par.general) return(model) } RMrotat <- new(CLASS_RM, .Data = RMrotat, type = c('shape function'), isotropy = c('cartesian system'), domain = c('single variable'), operator = FALSE, monotone = 'not monotone', finiterange = FALSE, simpleArguments = TRUE, maxdim = 3, vdim = 1 ) RMrotation <- function(phi) { cl <- match.call() submodels <- par.general <- par.model <- list() if (hasArg('phi') && !is.null(subst <- substitute(phi))) par.model[['phi']] <- CheckArg(phi, subst, TRUE) model <- methods::new('RMmodel', call = cl, name = 'RMrotation', submodels = submodels, par.model = par.model, par.general = par.general) return(model) } RMrotation <- new(CLASS_RM, .Data = RMrotation, type = c('shape function'), isotropy = c('cartesian system'), domain = c('single variable'), operator = FALSE, monotone = 'not monotone', finiterange = FALSE, simpleArguments = TRUE, maxdim = 3, vdim = -1 ) RMsign <- function(phi, p) { cl <- match.call() submodels <- par.general <- par.model <- list() if (hasArg(phi)) submodels[['phi']] <- phi if (hasArg('p') && !is.null(subst <- substitute(p))) par.model[['p']] <- CheckArg(p, subst, TRUE) model <- methods::new('RMmodel', call = cl, name = 'RMsign', submodels = submodels, par.model = par.model, par.general = par.general) return(model) } RMsign <- new(CLASS_RM, .Data = RMsign, type = c('shape function'), isotropy = c('framework dependent'), domain = c('single variable'), operator = TRUE, monotone = 'not monotone', finiterange = NA, simpleArguments = TRUE, maxdim = -3, vdim = 1 ) RMm2r <- function(phi) { cl <- match.call() submodels <- par.general <- par.model <- list() if (hasArg(phi)) submodels[['phi']] <- phi model <- methods::new('RMmodel', call = cl, name = 'RMm2r', submodels = submodels, par.model = par.model, par.general = par.general) return(model) } RMm2r <- new(CLASS_RM, .Data = RMm2r, type = c('shape function'), isotropy = c('isotropic'), domain = c('single variable'), operator = TRUE, monotone = 'submodel dependent monotonicity', finiterange = NA, simpleArguments = TRUE, maxdim = 3, vdim = 1 ) RMm3b <- function(phi) { cl <- match.call() submodels <- par.general <- par.model <- list() if (hasArg(phi)) submodels[['phi']] <- phi model <- methods::new('RMmodel', call = cl, name = 'RMm3b', submodels = submodels, par.model = par.model, par.general = par.general) return(model) } RMm3b <- new(CLASS_RM, .Data = RMm3b, type = c('shape function'), isotropy = c('isotropic'), domain = c('single variable'), operator = TRUE, monotone = 'monotone', finiterange = TRUE, simpleArguments = TRUE, maxdim = 3, vdim = 1 ) RMmps <- function(phi) { cl <- match.call() submodels <- par.general <- par.model <- list() if (hasArg(phi)) submodels[['phi']] <- phi model <- methods::new('RMmodel', call = cl, name = 'RMmps', submodels = submodels, par.model = par.model, par.general = par.general) return(model) } RMmps <- new(CLASS_RM, .Data = RMmps, type = c('shape function'), isotropy = c('cartesian system'), domain = c('single variable'), operator = TRUE, monotone = 'not monotone', finiterange = FALSE, simpleArguments = TRUE, maxdim = Inf, vdim = 1 ) RMtruncsupport <- function(phi, radius) { cl <- match.call() submodels <- par.general <- par.model <- list() if (hasArg(phi)) submodels[['phi']] <- phi if (hasArg('radius') && !is.null(subst <- substitute(radius))) par.model[['radius']] <- CheckArg(radius, subst, TRUE) model <- methods::new('RMmodel', call = cl, name = 'RMtruncsupport', submodels = submodels, par.model = par.model, par.general = par.general) return(model) } RMtruncsupport <- new(CLASS_RM, .Data = RMtruncsupport, type = c('shape function'), isotropy = c('framework dependent'), domain = c('single variable'), operator = TRUE, monotone = 'submodel dependent monotonicity', finiterange = NA, simpleArguments = TRUE, maxdim = -3, vdim = 1 ) RRdeterm <- function(mean) { cl <- match.call() submodels <- par.general <- par.model <- list() if (hasArg('mean') && !is.null(subst <- substitute(mean))) par.model[['mean']] <- CheckArg(mean, subst, FALSE) model <- methods::new('RMmodel', call = cl, name = 'RRdeterm', submodels = submodels, par.model = par.model, par.general = par.general) return(model) } RRdeterm <- new(CLASS_RM, .Data = RRdeterm, type = c('distribution family'), isotropy = c('cartesian system'), domain = c('single variable', 'kernel'), operator = FALSE, monotone = 'mismatch in monotonicity', finiterange = NA, simpleArguments = TRUE, maxdim = Inf, vdim = -3 ) RRgauss <- function(mu, sd, log) { cl <- match.call() submodels <- par.general <- par.model <- list() if (hasArg('mu') && !is.null(subst <- substitute(mu))) par.model[['mu']] <- CheckArg(mu, subst, FALSE) if (hasArg('sd') && !is.null(subst <- substitute(sd))) par.model[['sd']] <- CheckArg(sd, subst, FALSE) if (hasArg('log') && !is.null(subst <- substitute(log))) par.model[['log']] <- CheckArg(log, subst, FALSE) model <- methods::new('RMmodel', call = cl, name = 'RRgauss', submodels = submodels, par.model = par.model, par.general = par.general) return(model) } RRgauss <- new(CLASS_RM, .Data = RRgauss, type = c('distribution family'), isotropy = c('cartesian system'), domain = c('single variable', 'kernel'), operator = FALSE, monotone = 'mismatch in monotonicity', finiterange = FALSE, simpleArguments = TRUE, maxdim = Inf, vdim = -1 ) RRloc <- function(phi, mu, scale, pow) { cl <- match.call() submodels <- par.general <- par.model <- list() if (hasArg(phi)) submodels[['phi']] <- phi if (hasArg('mu') && !is.null(subst <- substitute(mu))) par.model[['mu']] <- CheckArg(mu, subst, FALSE) if (hasArg('scale') && !is.null(subst <- substitute(scale))) par.model[['scale']] <- CheckArg(scale, subst, FALSE) if (hasArg('pow') && !is.null(subst <- substitute(pow))) par.model[['pow']] <- CheckArg(pow, subst, FALSE) model <- methods::new('RMmodel', call = cl, name = 'RRloc', submodels = submodels, par.model = par.model, par.general = par.general) return(model) } RRloc <- new(CLASS_RM, .Data = RRloc, type = c('distribution family'), isotropy = c('cartesian system'), domain = c('single variable', 'kernel'), operator = TRUE, monotone = 'mismatch in monotonicity', finiterange = NA, simpleArguments = TRUE, maxdim = -3, vdim = -3 ) RRmcmc <- function(phi, mcmc_n, sigma, normed, maxdensity, rand.loc, gibbs) { cl <- match.call() submodels <- par.general <- par.model <- list() if (hasArg(phi)) submodels[['phi']] <- phi if (hasArg('mcmc_n') && !is.null(subst <- substitute(mcmc_n))) par.model[['mcmc_n']] <- CheckArg(mcmc_n, subst, FALSE) if (hasArg('sigma') && !is.null(subst <- substitute(sigma))) par.model[['sigma']] <- CheckArg(sigma, subst, FALSE) if (hasArg('normed') && !is.null(subst <- substitute(normed))) par.model[['normed']] <- CheckArg(normed, subst, FALSE) if (hasArg('maxdensity') && !is.null(subst <- substitute(maxdensity))) par.model[['maxdensity']] <- CheckArg(maxdensity, subst, FALSE) if (hasArg('rand.loc') && !is.null(subst <- substitute(rand.loc))) par.model[['rand.loc']] <- CheckArg(rand.loc, subst, FALSE) if (hasArg('gibbs') && !is.null(subst <- substitute(gibbs))) par.model[['gibbs']] <- CheckArg(gibbs, subst, FALSE) model <- methods::new('RMmodel', call = cl, name = 'RRmcmc', submodels = submodels, par.model = par.model, par.general = par.general) return(model) } RRmcmc <- new(CLASS_RM, .Data = RRmcmc, type = c('distribution family'), isotropy = c('cartesian system'), domain = c('single variable', 'kernel'), operator = TRUE, monotone = 'mismatch in monotonicity', finiterange = TRUE, simpleArguments = TRUE, maxdim = Inf, vdim = -1 ) RRrectangular <- function(phi, safety, minsteplen, maxsteps, parts, maxit, innermin, outermax, mcmc_n, normed, approx, onesided) { cl <- match.call() submodels <- par.general <- par.model <- list() if (hasArg(phi)) submodels[['phi']] <- phi if (hasArg('safety') && !is.null(subst <- substitute(safety))) par.model[['safety']] <- CheckArg(safety, subst, FALSE) if (hasArg('minsteplen') && !is.null(subst <- substitute(minsteplen))) par.model[['minsteplen']] <- CheckArg(minsteplen, subst, FALSE) if (hasArg('maxsteps') && !is.null(subst <- substitute(maxsteps))) par.model[['maxsteps']] <- CheckArg(maxsteps, subst, FALSE) if (hasArg('parts') && !is.null(subst <- substitute(parts))) par.model[['parts']] <- CheckArg(parts, subst, FALSE) if (hasArg('maxit') && !is.null(subst <- substitute(maxit))) par.model[['maxit']] <- CheckArg(maxit, subst, FALSE) if (hasArg('innermin') && !is.null(subst <- substitute(innermin))) par.model[['innermin']] <- CheckArg(innermin, subst, FALSE) if (hasArg('outermax') && !is.null(subst <- substitute(outermax))) par.model[['outermax']] <- CheckArg(outermax, subst, FALSE) if (hasArg('mcmc_n') && !is.null(subst <- substitute(mcmc_n))) par.model[['mcmc_n']] <- CheckArg(mcmc_n, subst, FALSE) if (hasArg('normed') && !is.null(subst <- substitute(normed))) par.model[['normed']] <- CheckArg(normed, subst, FALSE) if (hasArg('approx') && !is.null(subst <- substitute(approx))) par.model[['approx']] <- CheckArg(approx, subst, FALSE) if (hasArg('onesided') && !is.null(subst <- substitute(onesided))) par.model[['onesided']] <- CheckArg(onesided, subst, FALSE) model <- methods::new('RMmodel', call = cl, name = 'RRrectangular', submodels = submodels, par.model = par.model, par.general = par.general) return(model) } RRrectangular <- new(CLASS_RM, .Data = RRrectangular, type = c('distribution family'), isotropy = c('cartesian system'), domain = c('single variable', 'kernel'), operator = TRUE, monotone = 'mismatch in monotonicity', finiterange = TRUE, simpleArguments = TRUE, maxdim = Inf, vdim = -1 ) RRspheric <- function(spacedim, balldim, R) { cl <- match.call() submodels <- par.general <- par.model <- list() if (hasArg('spacedim') && !is.null(subst <- substitute(spacedim))) par.model[['spacedim']] <- CheckArg(spacedim, subst, FALSE) if (hasArg('balldim') && !is.null(subst <- substitute(balldim))) par.model[['balldim']] <- CheckArg(balldim, subst, FALSE) if (hasArg('R') && !is.null(subst <- substitute(R))) par.model[['R']] <- CheckArg(R, subst, FALSE) model <- methods::new('RMmodel', call = cl, name = 'RRspheric', submodels = submodels, par.model = par.model, par.general = par.general) return(model) } RRspheric <- new(CLASS_RM, .Data = RRspheric, type = c('distribution family'), isotropy = c('cartesian system'), domain = c('single variable'), operator = FALSE, monotone = 'mismatch in monotonicity', finiterange = TRUE, simpleArguments = TRUE, maxdim = 1, vdim = 1 ) RRunif <- function(min, max, normed) { cl <- match.call() submodels <- par.general <- par.model <- list() if (hasArg('min') && !is.null(subst <- substitute(min))) par.model[['min']] <- CheckArg(min, subst, FALSE) if (hasArg('max') && !is.null(subst <- substitute(max))) par.model[['max']] <- CheckArg(max, subst, FALSE) if (hasArg('normed') && !is.null(subst <- substitute(normed))) par.model[['normed']] <- CheckArg(normed, subst, FALSE) model <- methods::new('RMmodel', call = cl, name = 'RRunif', submodels = submodels, par.model = par.model, par.general = par.general) return(model) } RRunif <- new(CLASS_RM, .Data = RRunif, type = c('distribution family'), isotropy = c('cartesian system'), domain = c('single variable', 'kernel'), operator = FALSE, monotone = 'mismatch in monotonicity', finiterange = TRUE, simpleArguments = TRUE, maxdim = Inf, vdim = -1 ) RMmppplus <- function(C0, C1, C2, C3, C4, C5, C6, C7, C8, C9, p) { cl <- match.call() submodels <- par.general <- par.model <- list() if (hasArg(C0)) submodels[['C0']] <- C0 if (hasArg(C1)) submodels[['C1']] <- C1 if (hasArg(C2)) submodels[['C2']] <- C2 if (hasArg(C3)) submodels[['C3']] <- C3 if (hasArg(C4)) submodels[['C4']] <- C4 if (hasArg(C5)) submodels[['C5']] <- C5 if (hasArg(C6)) submodels[['C6']] <- C6 if (hasArg(C7)) submodels[['C7']] <- C7 if (hasArg(C8)) submodels[['C8']] <- C8 if (hasArg(C9)) submodels[['C9']] <- C9 if (hasArg('p') && !is.null(subst <- substitute(p))) par.model[['p']] <- CheckArg(p, subst, FALSE) model <- methods::new('RMmodel', call = cl, name = 'RMmppplus', submodels = submodels, par.model = par.model, par.general = par.general) return(model) } RMmppplus <- new(CLASS_RM, .Data = RMmppplus, type = c('point-shape function'), isotropy = c('framework dependent'), domain = c('single variable', 'kernel'), operator = TRUE, monotone = 'mismatch in monotonicity', finiterange = NA, simpleArguments = TRUE, maxdim = -3, vdim = -3 ) iRFcov <- function(phi) { cl <- match.call() submodels <- par.general <- par.model <- list() if (hasArg(phi)) submodels[['phi']] <- phi model <- methods::new('RMmodel', call = cl, name = 'RFcov', submodels = submodels, par.model = par.model, par.general = par.general) return(model) } iRFcov <- new(CLASS_RM, .Data = iRFcov, type = c('interface'), isotropy = c('non-dimension-reducing'), domain = c('single variable'), operator = TRUE, monotone = 'mismatch in monotonicity', finiterange = NA, simpleArguments = TRUE, maxdim = -3, vdim = -3 ) iRFcovmatrix <- function(phi) { cl <- match.call() submodels <- par.general <- par.model <- list() if (hasArg(phi)) submodels[['phi']] <- phi model <- methods::new('RMmodel', call = cl, name = 'RFcovmatrix', submodels = submodels, par.model = par.model, par.general = par.general) return(model) } iRFcovmatrix <- new(CLASS_RM, .Data = iRFcovmatrix, type = c('interface'), isotropy = c('non-dimension-reducing'), domain = c('single variable'), operator = TRUE, monotone = 'mismatch in monotonicity', finiterange = NA, simpleArguments = TRUE, maxdim = -3, vdim = -3 ) iRFloglikelihood <- function(phi, data, estimate_variance, betas_separate, ignore_trend) { cl <- match.call() submodels <- par.general <- par.model <- list() if (hasArg(phi)) submodels[['phi']] <- phi if (hasArg('data') && !is.null(subst <- substitute(data))) par.model[['data']] <- CheckArg(data, subst, FALSE) if (hasArg('estimate_variance') && !is.null(subst <- substitute(estimate_variance))) par.model[['estimate_variance']] <- CheckArg(estimate_variance, subst, FALSE) if (hasArg('betas_separate') && !is.null(subst <- substitute(betas_separate))) par.model[['betas_separate']] <- CheckArg(betas_separate, subst, FALSE) if (hasArg('ignore_trend') && !is.null(subst <- substitute(ignore_trend))) par.model[['ignore_trend']] <- CheckArg(ignore_trend, subst, FALSE) model <- methods::new('RMmodel', call = cl, name = 'RFloglikelihood', submodels = submodels, par.model = par.model, par.general = par.general) return(model) } iRFloglikelihood <- new(CLASS_RM, .Data = iRFloglikelihood, type = c('interface'), isotropy = c('non-dimension-reducing'), domain = c('single variable'), operator = TRUE, monotone = 'mismatch in monotonicity', finiterange = NA, simpleArguments = FALSE, maxdim = -3, vdim = -3 ) iRFpseudovariogra <- function(phi) { cl <- match.call() submodels <- par.general <- par.model <- list() if (hasArg(phi)) submodels[['phi']] <- phi model <- methods::new('RMmodel', call = cl, name = 'RFpseudovariogra', submodels = submodels, par.model = par.model, par.general = par.general) return(model) } iRFpseudovariogra <- new(CLASS_RM, .Data = iRFpseudovariogra, type = c('interface'), isotropy = c('non-dimension-reducing'), domain = c('single variable'), operator = TRUE, monotone = 'mismatch in monotonicity', finiterange = NA, simpleArguments = TRUE, maxdim = -3, vdim = -3 ) iRFvariogram <- function(phi) { cl <- match.call() submodels <- par.general <- par.model <- list() if (hasArg(phi)) submodels[['phi']] <- phi model <- methods::new('RMmodel', call = cl, name = 'RFvariogram', submodels = submodels, par.model = par.model, par.general = par.general) return(model) } iRFvariogram <- new(CLASS_RM, .Data = iRFvariogram, type = c('interface'), isotropy = c('non-dimension-reducing'), domain = c('single variable'), operator = TRUE, monotone = 'mismatch in monotonicity', finiterange = NA, simpleArguments = TRUE, maxdim = -3, vdim = -3 ) iRFsimulate <- function(phi, checkonly, setseed, env) { cl <- match.call() submodels <- par.general <- par.model <- list() if (hasArg(phi)) submodels[['phi']] <- phi if (hasArg('checkonly') && !is.null(subst <- substitute(checkonly))) par.model[['checkonly']] <- CheckArg(checkonly, subst, FALSE) if (hasArg('setseed') && !is.null(subst <- substitute(setseed))) par.model[['setseed']] <- CheckArg(setseed, subst, FALSE) if (hasArg('env') && !is.null(subst <- substitute(env))) par.model[['env']] <- CheckArg(env, subst, FALSE) model <- methods::new('RMmodel', call = cl, name = 'RFsimulate', submodels = submodels, par.model = par.model, par.general = par.general) return(model) } iRFsimulate <- new(CLASS_RM, .Data = iRFsimulate, type = c('interface'), isotropy = c('non-dimension-reducing'), domain = c('single variable'), operator = TRUE, monotone = 'mismatch in monotonicity', finiterange = NA, simpleArguments = FALSE, maxdim = -3, vdim = -3 ) RPtrend <- function(phi, mean) { cl <- match.call() submodels <- par.general <- par.model <- list() if (hasArg(phi)) submodels[['phi']] <- phi if (hasArg('mean') && !is.null(subst <- substitute(mean))) par.model[['mean']] <- CheckArg(mean, subst, FALSE) model <- methods::new('RMmodel', call = cl, name = 'RPtrend', submodels = submodels, par.model = par.model, par.general = par.general) return(model) } RPtrend <- new(CLASS_RM, .Data = RPtrend, type = c('process', 'method for Gauss process'), isotropy = c('non-dimension-reducing', 'non-dimension-reducing'), domain = c('single variable'), operator = TRUE, monotone = 'mismatch in monotonicity', finiterange = FALSE, simpleArguments = TRUE, maxdim = Inf, vdim = -3 ) RPaverage <- function(phi, shape, boxcox, intensity, method) { cl <- match.call() submodels <- par.general <- par.model <- list() if (hasArg(phi)) submodels[['phi']] <- phi if (hasArg(shape)) submodels[['shape']] <- shape if (hasArg('boxcox') && !is.null(subst <- substitute(boxcox))) par.model[['boxcox']] <- CheckArg(boxcox, subst, FALSE) if (hasArg('intensity') && !is.null(subst <- substitute(intensity))) par.model[['intensity']] <- CheckArg(intensity, subst, FALSE) if (hasArg('method') && !is.null(subst <- substitute(method))) par.model[['method']] <- CheckArg(method, subst, FALSE) model <- methods::new('RMmodel', call = cl, name = 'RPaverage', submodels = submodels, par.model = par.model, par.general = par.general) return(model) } RPaverage <- new(CLASS_RM, .Data = RPaverage, type = c('method for Gauss process'), isotropy = c('non-dimension-reducing'), domain = c('single variable'), operator = TRUE, monotone = 'mismatch in monotonicity', finiterange = FALSE, simpleArguments = TRUE, maxdim = 4, vdim = 1 ) RPcoins <- function(phi, shape, boxcox, intensity, method) { cl <- match.call() submodels <- par.general <- par.model <- list() if (hasArg(phi)) submodels[['phi']] <- phi if (hasArg(shape)) submodels[['shape']] <- shape if (hasArg('boxcox') && !is.null(subst <- substitute(boxcox))) par.model[['boxcox']] <- CheckArg(boxcox, subst, FALSE) if (hasArg('intensity') && !is.null(subst <- substitute(intensity))) par.model[['intensity']] <- CheckArg(intensity, subst, FALSE) if (hasArg('method') && !is.null(subst <- substitute(method))) par.model[['method']] <- CheckArg(method, subst, FALSE) model <- methods::new('RMmodel', call = cl, name = 'RPcoins', submodels = submodels, par.model = par.model, par.general = par.general) return(model) } RPcoins <- new(CLASS_RM, .Data = RPcoins, type = c('method for Gauss process'), isotropy = c('non-dimension-reducing'), domain = c('single variable'), operator = TRUE, monotone = 'mismatch in monotonicity', finiterange = FALSE, simpleArguments = TRUE, maxdim = 4, vdim = 1 ) RPcirculant <- function(phi, boxcox, force, mmin, strategy, maxGB, maxmem, tolIm, tolRe, trials, useprimes, dependent, approx_step, approx_maxgrid) { cl <- match.call() submodels <- par.general <- par.model <- list() if (hasArg(phi)) submodels[['phi']] <- phi if (hasArg('boxcox') && !is.null(subst <- substitute(boxcox))) par.model[['boxcox']] <- CheckArg(boxcox, subst, FALSE) if (hasArg('force') && !is.null(subst <- substitute(force))) par.model[['force']] <- CheckArg(force, subst, FALSE) if (hasArg('mmin') && !is.null(subst <- substitute(mmin))) par.model[['mmin']] <- CheckArg(mmin, subst, FALSE) if (hasArg('strategy') && !is.null(subst <- substitute(strategy))) par.model[['strategy']] <- CheckArg(strategy, subst, FALSE) if (hasArg('maxGB') && !is.null(subst <- substitute(maxGB))) par.model[['maxGB']] <- CheckArg(maxGB, subst, FALSE) if (hasArg('maxmem') && !is.null(subst <- substitute(maxmem))) par.model[['maxmem']] <- CheckArg(maxmem, subst, FALSE) if (hasArg('tolIm') && !is.null(subst <- substitute(tolIm))) par.model[['tolIm']] <- CheckArg(tolIm, subst, FALSE) if (hasArg('tolRe') && !is.null(subst <- substitute(tolRe))) par.model[['tolRe']] <- CheckArg(tolRe, subst, FALSE) if (hasArg('trials') && !is.null(subst <- substitute(trials))) par.model[['trials']] <- CheckArg(trials, subst, FALSE) if (hasArg('useprimes') && !is.null(subst <- substitute(useprimes))) par.model[['useprimes']] <- CheckArg(useprimes, subst, FALSE) if (hasArg('dependent') && !is.null(subst <- substitute(dependent))) par.model[['dependent']] <- CheckArg(dependent, subst, FALSE) if (hasArg('approx_step') && !is.null(subst <- substitute(approx_step))) par.model[['approx_step']] <- CheckArg(approx_step, subst, FALSE) if (hasArg('approx_maxgrid') && !is.null(subst <- substitute(approx_maxgrid))) par.model[['approx_maxgrid']] <- CheckArg(approx_maxgrid, subst, FALSE) model <- methods::new('RMmodel', call = cl, name = 'RPcirculant', submodels = submodels, par.model = par.model, par.general = par.general) return(model) } RPcirculant <- new(CLASS_RM, .Data = RPcirculant, type = c('method for Gauss process'), isotropy = c('non-dimension-reducing'), domain = c('single variable'), operator = TRUE, monotone = 'mismatch in monotonicity', finiterange = FALSE, simpleArguments = TRUE, maxdim = 13, vdim = -3 ) RPcutoff <- function(phi, boxcox, force, mmin, strategy, maxGB, maxmem, tolIm, tolRe, trials, useprimes, dependent, approx_step, approx_maxgrid, diameter, a) { cl <- match.call() submodels <- par.general <- par.model <- list() if (hasArg(phi)) submodels[['phi']] <- phi if (hasArg('boxcox') && !is.null(subst <- substitute(boxcox))) par.model[['boxcox']] <- CheckArg(boxcox, subst, FALSE) if (hasArg('force') && !is.null(subst <- substitute(force))) par.model[['force']] <- CheckArg(force, subst, FALSE) if (hasArg('mmin') && !is.null(subst <- substitute(mmin))) par.model[['mmin']] <- CheckArg(mmin, subst, FALSE) if (hasArg('strategy') && !is.null(subst <- substitute(strategy))) par.model[['strategy']] <- CheckArg(strategy, subst, FALSE) if (hasArg('maxGB') && !is.null(subst <- substitute(maxGB))) par.model[['maxGB']] <- CheckArg(maxGB, subst, FALSE) if (hasArg('maxmem') && !is.null(subst <- substitute(maxmem))) par.model[['maxmem']] <- CheckArg(maxmem, subst, FALSE) if (hasArg('tolIm') && !is.null(subst <- substitute(tolIm))) par.model[['tolIm']] <- CheckArg(tolIm, subst, FALSE) if (hasArg('tolRe') && !is.null(subst <- substitute(tolRe))) par.model[['tolRe']] <- CheckArg(tolRe, subst, FALSE) if (hasArg('trials') && !is.null(subst <- substitute(trials))) par.model[['trials']] <- CheckArg(trials, subst, FALSE) if (hasArg('useprimes') && !is.null(subst <- substitute(useprimes))) par.model[['useprimes']] <- CheckArg(useprimes, subst, FALSE) if (hasArg('dependent') && !is.null(subst <- substitute(dependent))) par.model[['dependent']] <- CheckArg(dependent, subst, FALSE) if (hasArg('approx_step') && !is.null(subst <- substitute(approx_step))) par.model[['approx_step']] <- CheckArg(approx_step, subst, FALSE) if (hasArg('approx_maxgrid') && !is.null(subst <- substitute(approx_maxgrid))) par.model[['approx_maxgrid']] <- CheckArg(approx_maxgrid, subst, FALSE) if (hasArg('diameter') && !is.null(subst <- substitute(diameter))) par.model[['diameter']] <- CheckArg(diameter, subst, FALSE) if (hasArg('a') && !is.null(subst <- substitute(a))) par.model[['a']] <- CheckArg(a, subst, FALSE) model <- methods::new('RMmodel', call = cl, name = 'RPcutoff', submodels = submodels, par.model = par.model, par.general = par.general) return(model) } RPcutoff <- new(CLASS_RM, .Data = RPcutoff, type = c('method for Gauss process', 'method for Gauss process'), isotropy = c('non-dimension-reducing', 'non-dimension-reducing'), domain = c('single variable'), operator = TRUE, monotone = 'mismatch in monotonicity', finiterange = FALSE, simpleArguments = TRUE, maxdim = 13, vdim = 1 ) RPintrinsic <- function(phi, boxcox, force, mmin, strategy, maxGB, maxmem, tolIm, tolRe, trials, useprimes, dependent, approx_step, approx_maxgrid, diameter, rawR) { cl <- match.call() submodels <- par.general <- par.model <- list() if (hasArg(phi)) submodels[['phi']] <- phi if (hasArg('boxcox') && !is.null(subst <- substitute(boxcox))) par.model[['boxcox']] <- CheckArg(boxcox, subst, FALSE) if (hasArg('force') && !is.null(subst <- substitute(force))) par.model[['force']] <- CheckArg(force, subst, FALSE) if (hasArg('mmin') && !is.null(subst <- substitute(mmin))) par.model[['mmin']] <- CheckArg(mmin, subst, FALSE) if (hasArg('strategy') && !is.null(subst <- substitute(strategy))) par.model[['strategy']] <- CheckArg(strategy, subst, FALSE) if (hasArg('maxGB') && !is.null(subst <- substitute(maxGB))) par.model[['maxGB']] <- CheckArg(maxGB, subst, FALSE) if (hasArg('maxmem') && !is.null(subst <- substitute(maxmem))) par.model[['maxmem']] <- CheckArg(maxmem, subst, FALSE) if (hasArg('tolIm') && !is.null(subst <- substitute(tolIm))) par.model[['tolIm']] <- CheckArg(tolIm, subst, FALSE) if (hasArg('tolRe') && !is.null(subst <- substitute(tolRe))) par.model[['tolRe']] <- CheckArg(tolRe, subst, FALSE) if (hasArg('trials') && !is.null(subst <- substitute(trials))) par.model[['trials']] <- CheckArg(trials, subst, FALSE) if (hasArg('useprimes') && !is.null(subst <- substitute(useprimes))) par.model[['useprimes']] <- CheckArg(useprimes, subst, FALSE) if (hasArg('dependent') && !is.null(subst <- substitute(dependent))) par.model[['dependent']] <- CheckArg(dependent, subst, FALSE) if (hasArg('approx_step') && !is.null(subst <- substitute(approx_step))) par.model[['approx_step']] <- CheckArg(approx_step, subst, FALSE) if (hasArg('approx_maxgrid') && !is.null(subst <- substitute(approx_maxgrid))) par.model[['approx_maxgrid']] <- CheckArg(approx_maxgrid, subst, FALSE) if (hasArg('diameter') && !is.null(subst <- substitute(diameter))) par.model[['diameter']] <- CheckArg(diameter, subst, FALSE) if (hasArg('rawR') && !is.null(subst <- substitute(rawR))) par.model[['rawR']] <- CheckArg(rawR, subst, FALSE) model <- methods::new('RMmodel', call = cl, name = 'RPintrinsic', submodels = submodels, par.model = par.model, par.general = par.general) return(model) } RPintrinsic <- new(CLASS_RM, .Data = RPintrinsic, type = c('method for Gauss process', 'method for Gauss process'), isotropy = c('non-dimension-reducing', 'non-dimension-reducing'), domain = c('single variable'), operator = TRUE, monotone = 'mismatch in monotonicity', finiterange = FALSE, simpleArguments = TRUE, maxdim = 13, vdim = 1 ) RPdirect <- function(phi, boxcox) { cl <- match.call() submodels <- par.general <- par.model <- list() if (hasArg(phi)) submodels[['phi']] <- phi if (hasArg('boxcox') && !is.null(subst <- substitute(boxcox))) par.model[['boxcox']] <- CheckArg(boxcox, subst, FALSE) model <- methods::new('RMmodel', call = cl, name = 'RPdirect', submodels = submodels, par.model = par.model, par.general = par.general) return(model) } RPdirect <- new(CLASS_RM, .Data = RPdirect, type = c('method for Gauss process'), isotropy = c('non-dimension-reducing'), domain = c('single variable'), operator = TRUE, monotone = 'mismatch in monotonicity', finiterange = FALSE, simpleArguments = TRUE, maxdim = Inf, vdim = -3 ) RPhyperplane <- function(phi, boxcox, superpos, maxlines, mar_distr, mar_param, additive) { cl <- match.call() submodels <- par.general <- par.model <- list() if (hasArg(phi)) submodels[['phi']] <- phi if (hasArg('boxcox') && !is.null(subst <- substitute(boxcox))) par.model[['boxcox']] <- CheckArg(boxcox, subst, FALSE) if (hasArg('superpos') && !is.null(subst <- substitute(superpos))) par.model[['superpos']] <- CheckArg(superpos, subst, FALSE) if (hasArg('maxlines') && !is.null(subst <- substitute(maxlines))) par.model[['maxlines']] <- CheckArg(maxlines, subst, FALSE) if (hasArg('mar_distr') && !is.null(subst <- substitute(mar_distr))) par.model[['mar_distr']] <- CheckArg(mar_distr, subst, FALSE) if (hasArg('mar_param') && !is.null(subst <- substitute(mar_param))) par.model[['mar_param']] <- CheckArg(mar_param, subst, FALSE) if (hasArg('additive') && !is.null(subst <- substitute(additive))) par.model[['additive']] <- CheckArg(additive, subst, FALSE) model <- methods::new('RMmodel', call = cl, name = 'RPhyperplane', submodels = submodels, par.model = par.model, par.general = par.general) return(model) } RPhyperplane <- new(CLASS_RM, .Data = RPhyperplane, type = c('method for Gauss process', 'method for Gauss process'), isotropy = c('non-dimension-reducing', 'non-dimension-reducing'), domain = c('single variable'), operator = TRUE, monotone = 'mismatch in monotonicity', finiterange = FALSE, simpleArguments = TRUE, maxdim = 2, vdim = 1 ) RPnugget <- function(phi, boxcox, tol, vdim) { cl <- match.call() submodels <- par.general <- par.model <- list() if (hasArg(phi)) submodels[['phi']] <- phi if (hasArg('boxcox') && !is.null(subst <- substitute(boxcox))) par.model[['boxcox']] <- CheckArg(boxcox, subst, FALSE) if (hasArg('tol') && !is.null(subst <- substitute(tol))) par.model[['tol']] <- CheckArg(tol, subst, FALSE) if (hasArg('vdim') && !is.null(subst <- substitute(vdim))) par.model[['vdim']] <- CheckArg(vdim, subst, FALSE) model <- methods::new('RMmodel', call = cl, name = 'RPnugget', submodels = submodels, par.model = par.model, par.general = par.general) return(model) } RPnugget <- new(CLASS_RM, .Data = RPnugget, type = c('method for Gauss process', 'method for Gauss process'), isotropy = c('non-dimension-reducing', 'non-dimension-reducing'), domain = c('single variable'), operator = TRUE, monotone = 'mismatch in monotonicity', finiterange = TRUE, simpleArguments = TRUE, maxdim = Inf, vdim = -2 ) RPsequential <- function(phi, boxcox, back_steps, initial) { cl <- match.call() submodels <- par.general <- par.model <- list() if (hasArg(phi)) submodels[['phi']] <- phi if (hasArg('boxcox') && !is.null(subst <- substitute(boxcox))) par.model[['boxcox']] <- CheckArg(boxcox, subst, FALSE) if (hasArg('back_steps') && !is.null(subst <- substitute(back_steps))) par.model[['back_steps']] <- CheckArg(back_steps, subst, FALSE) if (hasArg('initial') && !is.null(subst <- substitute(initial))) par.model[['initial']] <- CheckArg(initial, subst, FALSE) model <- methods::new('RMmodel', call = cl, name = 'RPsequential', submodels = submodels, par.model = par.model, par.general = par.general) return(model) } RPsequential <- new(CLASS_RM, .Data = RPsequential, type = c('method for Gauss process'), isotropy = c('non-dimension-reducing'), domain = c('single variable'), operator = TRUE, monotone = 'mismatch in monotonicity', finiterange = FALSE, simpleArguments = TRUE, maxdim = Inf, vdim = 1 ) RPspectral <- function(phi, boxcox, sp_lines, sp_grid, prop_factor, sigma) { cl <- match.call() submodels <- par.general <- par.model <- list() if (hasArg(phi)) submodels[['phi']] <- phi if (hasArg('boxcox') && !is.null(subst <- substitute(boxcox))) par.model[['boxcox']] <- CheckArg(boxcox, subst, FALSE) if (hasArg('sp_lines') && !is.null(subst <- substitute(sp_lines))) par.model[['sp_lines']] <- CheckArg(sp_lines, subst, FALSE) if (hasArg('sp_grid') && !is.null(subst <- substitute(sp_grid))) par.model[['sp_grid']] <- CheckArg(sp_grid, subst, FALSE) if (hasArg('prop_factor') && !is.null(subst <- substitute(prop_factor))) par.model[['prop_factor']] <- CheckArg(prop_factor, subst, FALSE) if (hasArg('sigma') && !is.null(subst <- substitute(sigma))) par.model[['sigma']] <- CheckArg(sigma, subst, FALSE) model <- methods::new('RMmodel', call = cl, name = 'RPspectral', submodels = submodels, par.model = par.model, par.general = par.general) return(model) } RPspectral <- new(CLASS_RM, .Data = RPspectral, type = c('method for Gauss process', 'method for Gauss process'), isotropy = c('non-dimension-reducing', 'non-dimension-reducing'), domain = c('single variable'), operator = TRUE, monotone = 'mismatch in monotonicity', finiterange = FALSE, simpleArguments = TRUE, maxdim = 4, vdim = 1 ) RPspecific <- function(phi, boxcox) { cl <- match.call() submodels <- par.general <- par.model <- list() if (hasArg(phi)) submodels[['phi']] <- phi if (hasArg('boxcox') && !is.null(subst <- substitute(boxcox))) par.model[['boxcox']] <- CheckArg(boxcox, subst, FALSE) model <- methods::new('RMmodel', call = cl, name = 'RPspecific', submodels = submodels, par.model = par.model, par.general = par.general) return(model) } RPspecific <- new(CLASS_RM, .Data = RPspecific, type = c('method for Gauss process'), isotropy = c('non-dimension-reducing'), domain = c('single variable'), operator = TRUE, monotone = 'mismatch in monotonicity', finiterange = FALSE, simpleArguments = TRUE, maxdim = 4, vdim = -3 ) RPtbm <- function(phi, boxcox, fulldim, reduceddim, layers, lines, linessimufactor, linesimustep, center, points) { cl <- match.call() submodels <- par.general <- par.model <- list() if (hasArg(phi)) submodels[['phi']] <- phi if (hasArg('boxcox') && !is.null(subst <- substitute(boxcox))) par.model[['boxcox']] <- CheckArg(boxcox, subst, FALSE) if (hasArg('fulldim') && !is.null(subst <- substitute(fulldim))) par.model[['fulldim']] <- CheckArg(fulldim, subst, FALSE) if (hasArg('reduceddim') && !is.null(subst <- substitute(reduceddim))) par.model[['reduceddim']] <- CheckArg(reduceddim, subst, FALSE) if (hasArg('layers') && !is.null(subst <- substitute(layers))) par.model[['layers']] <- CheckArg(layers, subst, FALSE) if (hasArg('lines') && !is.null(subst <- substitute(lines))) par.model[['lines']] <- CheckArg(lines, subst, FALSE) if (hasArg('linessimufactor') && !is.null(subst <- substitute(linessimufactor))) par.model[['linessimufactor']] <- CheckArg(linessimufactor, subst, FALSE) if (hasArg('linesimustep') && !is.null(subst <- substitute(linesimustep))) par.model[['linesimustep']] <- CheckArg(linesimustep, subst, FALSE) if (hasArg('center') && !is.null(subst <- substitute(center))) par.model[['center']] <- CheckArg(center, subst, FALSE) if (hasArg('points') && !is.null(subst <- substitute(points))) par.model[['points']] <- CheckArg(points, subst, FALSE) model <- methods::new('RMmodel', call = cl, name = 'RPtbm', submodels = submodels, par.model = par.model, par.general = par.general) return(model) } RPtbm <- new(CLASS_RM, .Data = RPtbm, type = c('method for Gauss process', 'method for Gauss process'), isotropy = c('non-dimension-reducing', 'non-dimension-reducing'), domain = c('single variable'), operator = TRUE, monotone = 'mismatch in monotonicity', finiterange = FALSE, simpleArguments = TRUE, maxdim = -3, vdim = -1 ) RPloggaussnormed <- function(variogram, prob, optimize_p, nth, burn.in, rejection) { cl <- match.call() submodels <- par.general <- par.model <- list() if (hasArg(variogram)) submodels[['variogram']] <- variogram if (hasArg('prob') && !is.null(subst <- substitute(prob))) par.model[['prob']] <- CheckArg(prob, subst, FALSE) if (hasArg('optimize_p') && !is.null(subst <- substitute(optimize_p))) par.model[['optimize_p']] <- CheckArg(optimize_p, subst, FALSE) if (hasArg('nth') && !is.null(subst <- substitute(nth))) par.model[['nth']] <- CheckArg(nth, subst, FALSE) if (hasArg('burn.in') && !is.null(subst <- substitute(burn.in))) par.model[['burn.in']] <- CheckArg(burn.in, subst, FALSE) if (hasArg('rejection') && !is.null(subst <- substitute(rejection))) par.model[['rejection']] <- CheckArg(rejection, subst, FALSE) model <- methods::new('RMmodel', call = cl, name = 'RPloggaussnormed', submodels = submodels, par.model = par.model, par.general = par.general) return(model) } RPloggaussnormed <- new(CLASS_RM, .Data = RPloggaussnormed, type = c('normed process (non-negative values with maximum value being 0 or 1)'), isotropy = c('non-dimension-reducing'), domain = c('single variable'), operator = TRUE, monotone = 'mismatch in monotonicity', finiterange = FALSE, simpleArguments = TRUE, maxdim = 4, vdim = -3 ) RPbrorig <- function(phi, tcf, xi, mu, s) { cl <- match.call() submodels <- par.general <- par.model <- list() if (hasArg(phi)) submodels[['phi']] <- phi if (hasArg(tcf)) submodels[['tcf']] <- tcf if (hasArg('xi') && !is.null(subst <- substitute(xi))) par.model[['xi']] <- CheckArg(xi, subst, FALSE) if (hasArg('mu') && !is.null(subst <- substitute(mu))) par.model[['mu']] <- CheckArg(mu, subst, FALSE) if (hasArg('s') && !is.null(subst <- substitute(s))) par.model[['s']] <- CheckArg(s, subst, FALSE) model <- methods::new('RMmodel', call = cl, name = 'RPbrorig', submodels = submodels, par.model = par.model, par.general = par.general) return(model) } RPbrorig <- new(CLASS_RM, .Data = RPbrorig, type = c('method for Brown-Resnick process'), isotropy = c('non-dimension-reducing'), domain = c('single variable'), operator = TRUE, monotone = 'mismatch in monotonicity', finiterange = FALSE, simpleArguments = TRUE, maxdim = 4, vdim = 1 ) RPbrmixed <- function(phi, tcf, xi, mu, s, meshsize, vertnumber, optim_mixed, optim_mixed_tol, lambda, areamat, variobound) { cl <- match.call() submodels <- par.general <- par.model <- list() if (hasArg(phi)) submodels[['phi']] <- phi if (hasArg(tcf)) submodels[['tcf']] <- tcf if (hasArg('xi') && !is.null(subst <- substitute(xi))) par.model[['xi']] <- CheckArg(xi, subst, FALSE) if (hasArg('mu') && !is.null(subst <- substitute(mu))) par.model[['mu']] <- CheckArg(mu, subst, FALSE) if (hasArg('s') && !is.null(subst <- substitute(s))) par.model[['s']] <- CheckArg(s, subst, FALSE) if (hasArg('meshsize') && !is.null(subst <- substitute(meshsize))) par.model[['meshsize']] <- CheckArg(meshsize, subst, FALSE) if (hasArg('vertnumber') && !is.null(subst <- substitute(vertnumber))) par.model[['vertnumber']] <- CheckArg(vertnumber, subst, FALSE) if (hasArg('optim_mixed') && !is.null(subst <- substitute(optim_mixed))) par.model[['optim_mixed']] <- CheckArg(optim_mixed, subst, FALSE) if (hasArg('optim_mixed_tol') && !is.null(subst <- substitute(optim_mixed_tol))) par.model[['optim_mixed_tol']] <- CheckArg(optim_mixed_tol, subst, FALSE) if (hasArg('lambda') && !is.null(subst <- substitute(lambda))) par.model[['lambda']] <- CheckArg(lambda, subst, FALSE) if (hasArg('areamat') && !is.null(subst <- substitute(areamat))) par.model[['areamat']] <- CheckArg(areamat, subst, FALSE) if (hasArg('variobound') && !is.null(subst <- substitute(variobound))) par.model[['variobound']] <- CheckArg(variobound, subst, FALSE) model <- methods::new('RMmodel', call = cl, name = 'RPbrmixed', submodels = submodels, par.model = par.model, par.general = par.general) return(model) } RPbrmixed <- new(CLASS_RM, .Data = RPbrmixed, type = c('method for Brown-Resnick process'), isotropy = c('non-dimension-reducing'), domain = c('single variable'), operator = TRUE, monotone = 'mismatch in monotonicity', finiterange = FALSE, simpleArguments = TRUE, maxdim = 4, vdim = -3 ) RPbrshifted <- function(phi, tcf, xi, mu, s) { cl <- match.call() submodels <- par.general <- par.model <- list() if (hasArg(phi)) submodels[['phi']] <- phi if (hasArg(tcf)) submodels[['tcf']] <- tcf if (hasArg('xi') && !is.null(subst <- substitute(xi))) par.model[['xi']] <- CheckArg(xi, subst, FALSE) if (hasArg('mu') && !is.null(subst <- substitute(mu))) par.model[['mu']] <- CheckArg(mu, subst, FALSE) if (hasArg('s') && !is.null(subst <- substitute(s))) par.model[['s']] <- CheckArg(s, subst, FALSE) model <- methods::new('RMmodel', call = cl, name = 'RPbrshifted', submodels = submodels, par.model = par.model, par.general = par.general) return(model) } RPbrshifted <- new(CLASS_RM, .Data = RPbrshifted, type = c('method for Brown-Resnick process'), isotropy = c('non-dimension-reducing'), domain = c('single variable'), operator = TRUE, monotone = 'mismatch in monotonicity', finiterange = FALSE, simpleArguments = TRUE, maxdim = 4, vdim = 1 ) RPbrownresnick <- function(phi, tcf, xi, mu, s) { cl <- match.call() submodels <- par.general <- par.model <- list() if (hasArg(phi)) submodels[['phi']] <- phi if (hasArg(tcf)) submodels[['tcf']] <- tcf if (hasArg('xi') && !is.null(subst <- substitute(xi))) par.model[['xi']] <- CheckArg(xi, subst, FALSE) if (hasArg('mu') && !is.null(subst <- substitute(mu))) par.model[['mu']] <- CheckArg(mu, subst, FALSE) if (hasArg('s') && !is.null(subst <- substitute(s))) par.model[['s']] <- CheckArg(s, subst, FALSE) model <- methods::new('RMmodel', call = cl, name = 'RPbrownresnick', submodels = submodels, par.model = par.model, par.general = par.general) return(model) } RPbrownresnick <- new(CLASS_RM, .Data = RPbrownresnick, type = c('method for Brown-Resnick process'), isotropy = c('non-dimension-reducing'), domain = c('single variable'), operator = TRUE, monotone = 'mismatch in monotonicity', finiterange = FALSE, simpleArguments = TRUE, maxdim = 4, vdim = 1 ) RPbernoulli <- function(phi, stationary_only, threshold) { cl <- match.call() submodels <- par.general <- par.model <- list() if (hasArg(phi)) submodels[['phi']] <- phi if (hasArg('stationary_only') && !is.null(subst <- substitute(stationary_only))) par.model[['stationary_only']] <- CheckArg(stationary_only, subst, FALSE) if (hasArg('threshold') && !is.null(subst <- substitute(threshold))) par.model[['threshold']] <- CheckArg(threshold, subst, FALSE) model <- methods::new('RMmodel', call = cl, name = 'RPbernoulli', submodels = submodels, par.model = par.model, par.general = par.general) return(model) } RPbernoulli <- new(CLASS_RM, .Data = RPbernoulli, type = c('normed process (non-negative values with maximum value being 0 or 1)'), isotropy = c('non-dimension-reducing'), domain = c('single variable'), operator = TRUE, monotone = 'mismatch in monotonicity', finiterange = FALSE, simpleArguments = TRUE, maxdim = Inf, vdim = -3 ) RPgauss <- function(phi, boxcox, stationary_only) { cl <- match.call() submodels <- par.general <- par.model <- list() if (hasArg(phi)) submodels[['phi']] <- phi if (hasArg('boxcox') && !is.null(subst <- substitute(boxcox))) par.model[['boxcox']] <- CheckArg(boxcox, subst, FALSE) if (hasArg('stationary_only') && !is.null(subst <- substitute(stationary_only))) par.model[['stationary_only']] <- CheckArg(stationary_only, subst, FALSE) model <- methods::new('RMmodel', call = cl, name = 'RPgauss', submodels = submodels, par.model = par.model, par.general = par.general) return(model) } RPgauss <- new(CLASS_RM, .Data = RPgauss, type = c('method for Gauss process'), isotropy = c('non-dimension-reducing'), domain = c('single variable'), operator = TRUE, monotone = 'mismatch in monotonicity', finiterange = FALSE, simpleArguments = TRUE, maxdim = Inf, vdim = -3 ) RPpoisson <- function(phi, intensity) { cl <- match.call() submodels <- par.general <- par.model <- list() if (hasArg(phi)) submodels[['phi']] <- phi if (hasArg('intensity') && !is.null(subst <- substitute(intensity))) par.model[['intensity']] <- CheckArg(intensity, subst, FALSE) model <- methods::new('RMmodel', call = cl, name = 'RPpoisson', submodels = submodels, par.model = par.model, par.general = par.general) return(model) } RPpoisson <- new(CLASS_RM, .Data = RPpoisson, type = c('Poisson'), isotropy = c('non-dimension-reducing'), domain = c('single variable'), operator = TRUE, monotone = 'mismatch in monotonicity', finiterange = FALSE, simpleArguments = TRUE, maxdim = 4, vdim = -3 ) RPschlather <- function(phi, tcf, xi, mu, s) { cl <- match.call() submodels <- par.general <- par.model <- list() if (hasArg(phi)) submodels[['phi']] <- phi if (hasArg(tcf)) submodels[['tcf']] <- tcf if (hasArg('xi') && !is.null(subst <- substitute(xi))) par.model[['xi']] <- CheckArg(xi, subst, FALSE) if (hasArg('mu') && !is.null(subst <- substitute(mu))) par.model[['mu']] <- CheckArg(mu, subst, FALSE) if (hasArg('s') && !is.null(subst <- substitute(s))) par.model[['s']] <- CheckArg(s, subst, FALSE) model <- methods::new('RMmodel', call = cl, name = 'RPschlather', submodels = submodels, par.model = par.model, par.general = par.general) return(model) } RPschlather <- new(CLASS_RM, .Data = RPschlather, type = c('Schlather'), isotropy = c('non-dimension-reducing'), domain = c('single variable'), operator = TRUE, monotone = 'mismatch in monotonicity', finiterange = FALSE, simpleArguments = TRUE, maxdim = Inf, vdim = 1 ) RPopitz <- function(phi, xi, mu, s, alpha) { cl <- match.call() submodels <- par.general <- par.model <- list() if (hasArg(phi)) submodels[['phi']] <- phi if (hasArg('xi') && !is.null(subst <- substitute(xi))) par.model[['xi']] <- CheckArg(xi, subst, FALSE) if (hasArg('mu') && !is.null(subst <- substitute(mu))) par.model[['mu']] <- CheckArg(mu, subst, FALSE) if (hasArg('s') && !is.null(subst <- substitute(s))) par.model[['s']] <- CheckArg(s, subst, FALSE) if (hasArg('alpha') && !is.null(subst <- substitute(alpha))) par.model[['alpha']] <- CheckArg(alpha, subst, FALSE) model <- methods::new('RMmodel', call = cl, name = 'RPopitz', submodels = submodels, par.model = par.model, par.general = par.general) return(model) } RPopitz <- new(CLASS_RM, .Data = RPopitz, type = c('Schlather'), isotropy = c('non-dimension-reducing'), domain = c('single variable'), operator = TRUE, monotone = 'mismatch in monotonicity', finiterange = FALSE, simpleArguments = TRUE, maxdim = Inf, vdim = 1 ) RPsmith <- function(shape, tcf, xi, mu, s) { cl <- match.call() submodels <- par.general <- par.model <- list() if (hasArg(shape)) submodels[['shape']] <- shape if (hasArg(tcf)) submodels[['tcf']] <- tcf if (hasArg('xi') && !is.null(subst <- substitute(xi))) par.model[['xi']] <- CheckArg(xi, subst, FALSE) if (hasArg('mu') && !is.null(subst <- substitute(mu))) par.model[['mu']] <- CheckArg(mu, subst, FALSE) if (hasArg('s') && !is.null(subst <- substitute(s))) par.model[['s']] <- CheckArg(s, subst, FALSE) model <- methods::new('RMmodel', call = cl, name = 'RPsmith', submodels = submodels, par.model = par.model, par.general = par.general) return(model) } RPsmith <- new(CLASS_RM, .Data = RPsmith, type = c('Smith'), isotropy = c('non-dimension-reducing'), domain = c('single variable'), operator = TRUE, monotone = 'mismatch in monotonicity', finiterange = FALSE, simpleArguments = TRUE, maxdim = 4, vdim = 1 ) RPchi2 <- function(phi, boxcox, f) { cl <- match.call() submodels <- par.general <- par.model <- list() if (hasArg(phi)) submodels[['phi']] <- phi if (hasArg('boxcox') && !is.null(subst <- substitute(boxcox))) par.model[['boxcox']] <- CheckArg(boxcox, subst, FALSE) if (hasArg('f') && !is.null(subst <- substitute(f))) par.model[['f']] <- CheckArg(f, subst, FALSE) model <- methods::new('RMmodel', call = cl, name = 'RPchi2', submodels = submodels, par.model = par.model, par.general = par.general) return(model) } RPchi2 <- new(CLASS_RM, .Data = RPchi2, type = c('process'), isotropy = c('non-dimension-reducing'), domain = c('single variable'), operator = TRUE, monotone = 'mismatch in monotonicity', finiterange = FALSE, simpleArguments = TRUE, maxdim = Inf, vdim = -3 ) RPt <- function(phi, boxcox, nu) { cl <- match.call() submodels <- par.general <- par.model <- list() if (hasArg(phi)) submodels[['phi']] <- phi if (hasArg('boxcox') && !is.null(subst <- substitute(boxcox))) par.model[['boxcox']] <- CheckArg(boxcox, subst, FALSE) if (hasArg('nu') && !is.null(subst <- substitute(nu))) par.model[['nu']] <- CheckArg(nu, subst, FALSE) model <- methods::new('RMmodel', call = cl, name = 'RPt', submodels = submodels, par.model = par.model, par.general = par.general) return(model) } RPt <- new(CLASS_RM, .Data = RPt, type = c('process'), isotropy = c('non-dimension-reducing'), domain = c('single variable'), operator = TRUE, monotone = 'mismatch in monotonicity', finiterange = FALSE, simpleArguments = TRUE, maxdim = Inf, vdim = -3 ) R.minus <- function(x, y, factor) { cl <- match.call() submodels <- par.general <- par.model <- list() if (hasArg('x') && !is.null(subst <- substitute(x))) par.model[['x']] <- CheckMaths(x, subst, TRUE) if (hasArg('y') && !is.null(subst <- substitute(y))) par.model[['y']] <- CheckMaths(y, subst, TRUE) if (hasArg('factor') && !is.null(subst <- substitute(factor))) par.model[['factor']] <- CheckMaths(factor, subst, TRUE) model <- methods::new('RMmodel', call = cl, name = 'R.minus', submodels = submodels, par.model = par.model, par.general = par.general) return(model) } R.minus <- new(CLASS_RM, .Data = R.minus, type = c('shape function', 'trend'), isotropy = c('framework dependent', 'framework dependent'), domain = c('single variable'), operator = FALSE, monotone = 'not monotone', finiterange = FALSE, simpleArguments = TRUE, maxdim = -2, vdim = 1 ) R.plus <- function(x, y, factor) { cl <- match.call() submodels <- par.general <- par.model <- list() if (hasArg('x') && !is.null(subst <- substitute(x))) par.model[['x']] <- CheckMaths(x, subst, FALSE) if (hasArg('y') && !is.null(subst <- substitute(y))) par.model[['y']] <- CheckMaths(y, subst, FALSE) if (hasArg('factor') && !is.null(subst <- substitute(factor))) par.model[['factor']] <- CheckMaths(factor, subst, FALSE) model <- methods::new('RMmodel', call = cl, name = 'R.plus', submodels = submodels, par.model = par.model, par.general = par.general) return(model) } R.plus <- new(CLASS_RM, .Data = R.plus, type = c('mathematical operator', 'trend'), isotropy = c('framework dependent', 'framework dependent'), domain = c('single variable'), operator = FALSE, monotone = 'not monotone', finiterange = FALSE, simpleArguments = TRUE, maxdim = 1, vdim = 1 ) R.div <- function(x, y, factor) { cl <- match.call() submodels <- par.general <- par.model <- list() if (hasArg('x') && !is.null(subst <- substitute(x))) par.model[['x']] <- CheckMaths(x, subst, FALSE) if (hasArg('y') && !is.null(subst <- substitute(y))) par.model[['y']] <- CheckMaths(y, subst, FALSE) if (hasArg('factor') && !is.null(subst <- substitute(factor))) par.model[['factor']] <- CheckMaths(factor, subst, FALSE) model <- methods::new('RMmodel', call = cl, name = 'R.div', submodels = submodels, par.model = par.model, par.general = par.general) return(model) } R.div <- new(CLASS_RM, .Data = R.div, type = c('mathematical operator', 'trend'), isotropy = c('framework dependent', 'framework dependent'), domain = c('single variable'), operator = FALSE, monotone = 'not monotone', finiterange = FALSE, simpleArguments = TRUE, maxdim = 1, vdim = 1 ) R.mult <- function(x, y, factor) { cl <- match.call() submodels <- par.general <- par.model <- list() if (hasArg('x') && !is.null(subst <- substitute(x))) par.model[['x']] <- CheckMaths(x, subst, FALSE) if (hasArg('y') && !is.null(subst <- substitute(y))) par.model[['y']] <- CheckMaths(y, subst, FALSE) if (hasArg('factor') && !is.null(subst <- substitute(factor))) par.model[['factor']] <- CheckMaths(factor, subst, FALSE) model <- methods::new('RMmodel', call = cl, name = 'R.mult', submodels = submodels, par.model = par.model, par.general = par.general) return(model) } R.mult <- new(CLASS_RM, .Data = R.mult, type = c('mathematical operator', 'trend'), isotropy = c('framework dependent', 'framework dependent'), domain = c('single variable'), operator = FALSE, monotone = 'not monotone', finiterange = FALSE, simpleArguments = TRUE, maxdim = 1, vdim = 1 ) R.const <- function(x) { cl <- match.call() submodels <- par.general <- par.model <- list() if (hasArg('x') && !is.null(subst <- substitute(x))) par.model[['x']] <- CheckMaths(x, subst, TRUE) model <- methods::new('RMmodel', call = cl, name = 'R.const', submodels = submodels, par.model = par.model, par.general = par.general) return(model) } R.const <- new(CLASS_RM, .Data = R.const, type = c('mathematical operator', 'trend', 'negative definite', 'tail correlation'), isotropy = c('framework dependent', 'framework dependent', 'framework dependent', 'framework dependent'), domain = c('single variable'), operator = FALSE, monotone = 'not monotone', finiterange = FALSE, simpleArguments = TRUE, maxdim = -2, vdim = 1 ) R.p <- function(proj, new, factor) { cl <- match.call() submodels <- par.general <- par.model <- list() if (hasArg('proj') && !is.null(subst <- substitute(proj))) par.model[['proj']] <- CheckMixed(proj, subst, PROJECTION_NAMES) if (!(hasArg('new') && !is.null(subst <- substitute(new)))) new <- UNREDUCED par.model[['new']] <- CheckChar(new, subst, ISO_NAMES, FALSE) if (hasArg('factor') && !is.null(subst <- substitute(factor))) par.model[['factor']] <- CheckMaths(factor, subst, FALSE) model <- methods::new('RMmodel', call = cl, name = 'R.p', submodels = submodels, par.model = par.model, par.general = par.general) return(model) } R.p <- new(CLASS_RM, .Data = R.p, type = c('mathematical operator', 'trend'), isotropy = c('parameter dependent', 'framework dependent'), domain = c('single variable'), operator = FALSE, monotone = 'not monotone', finiterange = FALSE, simpleArguments = TRUE, maxdim = Inf, vdim = 1 ) R.c <- function(a, b, c, d, e, f, g, h, i, j, l, m, n, o, p, q, ncol, factor) { cl <- match.call() submodels <- par.general <- par.model <- list() if (hasArg('a') && !is.null(subst <- substitute(a))) par.model[['a']] <- CheckMaths(a, subst, TRUE) if (hasArg('b') && !is.null(subst <- substitute(b))) par.model[['b']] <- CheckMaths(b, subst, TRUE) if (hasArg('c') && !is.null(subst <- substitute(c))) par.model[['c']] <- CheckMaths(c, subst, TRUE) if (hasArg('d') && !is.null(subst <- substitute(d))) par.model[['d']] <- CheckMaths(d, subst, TRUE) if (hasArg('e') && !is.null(subst <- substitute(e))) par.model[['e']] <- CheckMaths(e, subst, TRUE) if (hasArg('f') && !is.null(subst <- substitute(f))) par.model[['f']] <- CheckMaths(f, subst, TRUE) if (hasArg('g') && !is.null(subst <- substitute(g))) par.model[['g']] <- CheckMaths(g, subst, TRUE) if (hasArg('h') && !is.null(subst <- substitute(h))) par.model[['h']] <- CheckMaths(h, subst, TRUE) if (hasArg('i') && !is.null(subst <- substitute(i))) par.model[['i']] <- CheckMaths(i, subst, TRUE) if (hasArg('j') && !is.null(subst <- substitute(j))) par.model[['j']] <- CheckMaths(j, subst, TRUE) if (hasArg('l') && !is.null(subst <- substitute(l))) par.model[['l']] <- CheckMaths(l, subst, TRUE) if (hasArg('m') && !is.null(subst <- substitute(m))) par.model[['m']] <- CheckMaths(m, subst, TRUE) if (hasArg('n') && !is.null(subst <- substitute(n))) par.model[['n']] <- CheckMaths(n, subst, TRUE) if (hasArg('o') && !is.null(subst <- substitute(o))) par.model[['o']] <- CheckMaths(o, subst, TRUE) if (hasArg('p') && !is.null(subst <- substitute(p))) par.model[['p']] <- CheckMaths(p, subst, TRUE) if (hasArg('q') && !is.null(subst <- substitute(q))) par.model[['q']] <- CheckMaths(q, subst, TRUE) if (hasArg('ncol') && !is.null(subst <- substitute(ncol))) par.model[['ncol']] <- CheckMaths(ncol, subst, TRUE) if (hasArg('factor') && !is.null(subst <- substitute(factor))) par.model[['factor']] <- CheckMaths(factor, subst, TRUE) model <- methods::new('RMmodel', call = cl, name = 'R.c', submodels = submodels, par.model = par.model, par.general = par.general) return(model) } R.c <- new(CLASS_RM, .Data = R.c, type = c('shape function', 'trend'), isotropy = c('submodel dependent', 'submodel dependent'), domain = c('submodel dependent'), operator = FALSE, monotone = 'not monotone', finiterange = FALSE, simpleArguments = TRUE, maxdim = 1, vdim = -1 ) R.is <- function(x, is, y) { cl <- match.call() submodels <- par.general <- par.model <- list() if (hasArg('x') && !is.null(subst <- substitute(x))) par.model[['x']] <- CheckMaths(x, subst, TRUE) if (hasArg('is') && !is.null(subst <- substitute(is))) par.model[['is']] <- CheckChar(is, subst, EQ_NAMES, TRUE) if (hasArg('y') && !is.null(subst <- substitute(y))) par.model[['y']] <- CheckMaths(y, subst, TRUE) model <- methods::new('RMmodel', call = cl, name = 'R.is', submodels = submodels, par.model = par.model, par.general = par.general) return(model) } R.is <- new(CLASS_RM, .Data = R.is, type = c('shape function', 'trend'), isotropy = c('framework dependent', 'framework dependent'), domain = c('single variable'), operator = FALSE, monotone = 'not monotone', finiterange = FALSE, simpleArguments = TRUE, maxdim = 1, vdim = 1 ) R.asin <- function(x) { cl <- match.call() submodels <- par.general <- par.model <- list() if (hasArg('x') && !is.null(subst <- substitute(x))) par.model[['x']] <- CheckMaths(x, subst, TRUE) model <- methods::new('RMmodel', call = cl, name = 'R.asin', submodels = submodels, par.model = par.model, par.general = par.general) return(model) } R.asin <- new(CLASS_RM, .Data = R.asin, type = c('shape function', 'trend'), isotropy = c('framework dependent', 'framework dependent'), domain = c('single variable'), operator = FALSE, monotone = 'not monotone', finiterange = FALSE, simpleArguments = TRUE, maxdim = -2, vdim = 1 ) R.atan <- function(x) { cl <- match.call() submodels <- par.general <- par.model <- list() if (hasArg('x') && !is.null(subst <- substitute(x))) par.model[['x']] <- CheckMaths(x, subst, TRUE) model <- methods::new('RMmodel', call = cl, name = 'R.atan', submodels = submodels, par.model = par.model, par.general = par.general) return(model) } R.atan <- new(CLASS_RM, .Data = R.atan, type = c('shape function', 'trend'), isotropy = c('framework dependent', 'framework dependent'), domain = c('single variable'), operator = FALSE, monotone = 'not monotone', finiterange = FALSE, simpleArguments = TRUE, maxdim = -2, vdim = 1 ) R.atan2 <- function(y, x) { cl <- match.call() submodels <- par.general <- par.model <- list() if (hasArg('y') && !is.null(subst <- substitute(y))) par.model[['y']] <- CheckMaths(y, subst, TRUE) if (hasArg('x') && !is.null(subst <- substitute(x))) par.model[['x']] <- CheckMaths(x, subst, TRUE) model <- methods::new('RMmodel', call = cl, name = 'R.atan2', submodels = submodels, par.model = par.model, par.general = par.general) return(model) } R.atan2 <- new(CLASS_RM, .Data = R.atan2, type = c('shape function', 'trend'), isotropy = c('framework dependent', 'framework dependent'), domain = c('single variable'), operator = FALSE, monotone = 'not monotone', finiterange = FALSE, simpleArguments = TRUE, maxdim = -2, vdim = 1 ) R.cos <- function(x) { cl <- match.call() submodels <- par.general <- par.model <- list() if (hasArg('x') && !is.null(subst <- substitute(x))) par.model[['x']] <- CheckMaths(x, subst, TRUE) model <- methods::new('RMmodel', call = cl, name = 'R.cos', submodels = submodels, par.model = par.model, par.general = par.general) return(model) } R.cos <- new(CLASS_RM, .Data = R.cos, type = c('shape function', 'trend'), isotropy = c('framework dependent', 'framework dependent'), domain = c('single variable'), operator = FALSE, monotone = 'not monotone', finiterange = FALSE, simpleArguments = TRUE, maxdim = -2, vdim = 1 ) R.sin <- function(x) { cl <- match.call() submodels <- par.general <- par.model <- list() if (hasArg('x') && !is.null(subst <- substitute(x))) par.model[['x']] <- CheckMaths(x, subst, TRUE) model <- methods::new('RMmodel', call = cl, name = 'R.sin', submodels = submodels, par.model = par.model, par.general = par.general) return(model) } R.sin <- new(CLASS_RM, .Data = R.sin, type = c('shape function', 'trend'), isotropy = c('framework dependent', 'framework dependent'), domain = c('single variable'), operator = FALSE, monotone = 'not monotone', finiterange = FALSE, simpleArguments = TRUE, maxdim = -2, vdim = 1 ) R.tan <- function(x) { cl <- match.call() submodels <- par.general <- par.model <- list() if (hasArg('x') && !is.null(subst <- substitute(x))) par.model[['x']] <- CheckMaths(x, subst, TRUE) model <- methods::new('RMmodel', call = cl, name = 'R.tan', submodels = submodels, par.model = par.model, par.general = par.general) return(model) } R.tan <- new(CLASS_RM, .Data = R.tan, type = c('shape function', 'trend'), isotropy = c('framework dependent', 'framework dependent'), domain = c('single variable'), operator = FALSE, monotone = 'not monotone', finiterange = FALSE, simpleArguments = TRUE, maxdim = -2, vdim = 1 ) R.asinh <- function(x) { cl <- match.call() submodels <- par.general <- par.model <- list() if (hasArg('x') && !is.null(subst <- substitute(x))) par.model[['x']] <- CheckMaths(x, subst, TRUE) model <- methods::new('RMmodel', call = cl, name = 'R.asinh', submodels = submodels, par.model = par.model, par.general = par.general) return(model) } R.asinh <- new(CLASS_RM, .Data = R.asinh, type = c('shape function', 'trend'), isotropy = c('framework dependent', 'framework dependent'), domain = c('single variable'), operator = FALSE, monotone = 'not monotone', finiterange = FALSE, simpleArguments = TRUE, maxdim = -2, vdim = 1 ) R.atanh <- function(x) { cl <- match.call() submodels <- par.general <- par.model <- list() if (hasArg('x') && !is.null(subst <- substitute(x))) par.model[['x']] <- CheckMaths(x, subst, TRUE) model <- methods::new('RMmodel', call = cl, name = 'R.atanh', submodels = submodels, par.model = par.model, par.general = par.general) return(model) } R.atanh <- new(CLASS_RM, .Data = R.atanh, type = c('shape function', 'trend'), isotropy = c('framework dependent', 'framework dependent'), domain = c('single variable'), operator = FALSE, monotone = 'not monotone', finiterange = FALSE, simpleArguments = TRUE, maxdim = -2, vdim = 1 ) R.cosh <- function(x) { cl <- match.call() submodels <- par.general <- par.model <- list() if (hasArg('x') && !is.null(subst <- substitute(x))) par.model[['x']] <- CheckMaths(x, subst, TRUE) model <- methods::new('RMmodel', call = cl, name = 'R.cosh', submodels = submodels, par.model = par.model, par.general = par.general) return(model) } R.cosh <- new(CLASS_RM, .Data = R.cosh, type = c('shape function', 'trend'), isotropy = c('framework dependent', 'framework dependent'), domain = c('single variable'), operator = FALSE, monotone = 'not monotone', finiterange = FALSE, simpleArguments = TRUE, maxdim = -2, vdim = 1 ) R.sinh <- function(x) { cl <- match.call() submodels <- par.general <- par.model <- list() if (hasArg('x') && !is.null(subst <- substitute(x))) par.model[['x']] <- CheckMaths(x, subst, TRUE) model <- methods::new('RMmodel', call = cl, name = 'R.sinh', submodels = submodels, par.model = par.model, par.general = par.general) return(model) } R.sinh <- new(CLASS_RM, .Data = R.sinh, type = c('shape function', 'trend'), isotropy = c('framework dependent', 'framework dependent'), domain = c('single variable'), operator = FALSE, monotone = 'not monotone', finiterange = FALSE, simpleArguments = TRUE, maxdim = -2, vdim = 1 ) R.tanh <- function(x) { cl <- match.call() submodels <- par.general <- par.model <- list() if (hasArg('x') && !is.null(subst <- substitute(x))) par.model[['x']] <- CheckMaths(x, subst, TRUE) model <- methods::new('RMmodel', call = cl, name = 'R.tanh', submodels = submodels, par.model = par.model, par.general = par.general) return(model) } R.tanh <- new(CLASS_RM, .Data = R.tanh, type = c('shape function', 'trend'), isotropy = c('framework dependent', 'framework dependent'), domain = c('single variable'), operator = FALSE, monotone = 'not monotone', finiterange = FALSE, simpleArguments = TRUE, maxdim = -2, vdim = 1 ) R.log <- function(x) { cl <- match.call() submodels <- par.general <- par.model <- list() if (hasArg('x') && !is.null(subst <- substitute(x))) par.model[['x']] <- CheckMaths(x, subst, TRUE) model <- methods::new('RMmodel', call = cl, name = 'R.log', submodels = submodels, par.model = par.model, par.general = par.general) return(model) } R.log <- new(CLASS_RM, .Data = R.log, type = c('shape function', 'trend'), isotropy = c('framework dependent', 'framework dependent'), domain = c('single variable'), operator = FALSE, monotone = 'not monotone', finiterange = FALSE, simpleArguments = TRUE, maxdim = -2, vdim = 1 ) R.expm1 <- function(x) { cl <- match.call() submodels <- par.general <- par.model <- list() if (hasArg('x') && !is.null(subst <- substitute(x))) par.model[['x']] <- CheckMaths(x, subst, TRUE) model <- methods::new('RMmodel', call = cl, name = 'R.expm1', submodels = submodels, par.model = par.model, par.general = par.general) return(model) } R.expm1 <- new(CLASS_RM, .Data = R.expm1, type = c('shape function', 'trend'), isotropy = c('framework dependent', 'framework dependent'), domain = c('single variable'), operator = FALSE, monotone = 'not monotone', finiterange = FALSE, simpleArguments = TRUE, maxdim = -2, vdim = 1 ) R.log1p <- function(x) { cl <- match.call() submodels <- par.general <- par.model <- list() if (hasArg('x') && !is.null(subst <- substitute(x))) par.model[['x']] <- CheckMaths(x, subst, TRUE) model <- methods::new('RMmodel', call = cl, name = 'R.log1p', submodels = submodels, par.model = par.model, par.general = par.general) return(model) } R.log1p <- new(CLASS_RM, .Data = R.log1p, type = c('shape function', 'trend'), isotropy = c('framework dependent', 'framework dependent'), domain = c('single variable'), operator = FALSE, monotone = 'not monotone', finiterange = FALSE, simpleArguments = TRUE, maxdim = -2, vdim = 1 ) R.exp2 <- function(x) { cl <- match.call() submodels <- par.general <- par.model <- list() if (hasArg('x') && !is.null(subst <- substitute(x))) par.model[['x']] <- CheckMaths(x, subst, TRUE) model <- methods::new('RMmodel', call = cl, name = 'R.exp2', submodels = submodels, par.model = par.model, par.general = par.general) return(model) } R.exp2 <- new(CLASS_RM, .Data = R.exp2, type = c('shape function', 'trend'), isotropy = c('framework dependent', 'framework dependent'), domain = c('single variable'), operator = FALSE, monotone = 'not monotone', finiterange = FALSE, simpleArguments = TRUE, maxdim = -2, vdim = 1 ) R.log2 <- function(x) { cl <- match.call() submodels <- par.general <- par.model <- list() if (hasArg('x') && !is.null(subst <- substitute(x))) par.model[['x']] <- CheckMaths(x, subst, TRUE) model <- methods::new('RMmodel', call = cl, name = 'R.log2', submodels = submodels, par.model = par.model, par.general = par.general) return(model) } R.log2 <- new(CLASS_RM, .Data = R.log2, type = c('shape function', 'trend'), isotropy = c('framework dependent', 'framework dependent'), domain = c('single variable'), operator = FALSE, monotone = 'not monotone', finiterange = FALSE, simpleArguments = TRUE, maxdim = -2, vdim = 1 ) R.hypot <- function(x, y) { cl <- match.call() submodels <- par.general <- par.model <- list() if (hasArg('x') && !is.null(subst <- substitute(x))) par.model[['x']] <- CheckMaths(x, subst, TRUE) if (hasArg('y') && !is.null(subst <- substitute(y))) par.model[['y']] <- CheckMaths(y, subst, TRUE) model <- methods::new('RMmodel', call = cl, name = 'R.hypot', submodels = submodels, par.model = par.model, par.general = par.general) return(model) } R.hypot <- new(CLASS_RM, .Data = R.hypot, type = c('shape function', 'trend'), isotropy = c('framework dependent', 'framework dependent'), domain = c('single variable'), operator = FALSE, monotone = 'not monotone', finiterange = FALSE, simpleArguments = TRUE, maxdim = -2, vdim = 1 ) R.cbrt <- function(x) { cl <- match.call() submodels <- par.general <- par.model <- list() if (hasArg('x') && !is.null(subst <- substitute(x))) par.model[['x']] <- CheckMaths(x, subst, TRUE) model <- methods::new('RMmodel', call = cl, name = 'R.cbrt', submodels = submodels, par.model = par.model, par.general = par.general) return(model) } R.cbrt <- new(CLASS_RM, .Data = R.cbrt, type = c('shape function', 'trend'), isotropy = c('framework dependent', 'framework dependent'), domain = c('single variable'), operator = FALSE, monotone = 'not monotone', finiterange = FALSE, simpleArguments = TRUE, maxdim = -2, vdim = 1 ) R.ceil <- function(x) { cl <- match.call() submodels <- par.general <- par.model <- list() if (hasArg('x') && !is.null(subst <- substitute(x))) par.model[['x']] <- CheckMaths(x, subst, TRUE) model <- methods::new('RMmodel', call = cl, name = 'R.ceil', submodels = submodels, par.model = par.model, par.general = par.general) return(model) } R.ceil <- new(CLASS_RM, .Data = R.ceil, type = c('shape function', 'trend'), isotropy = c('framework dependent', 'framework dependent'), domain = c('single variable'), operator = FALSE, monotone = 'not monotone', finiterange = FALSE, simpleArguments = TRUE, maxdim = -2, vdim = 1 ) R.floor <- function(x) { cl <- match.call() submodels <- par.general <- par.model <- list() if (hasArg('x') && !is.null(subst <- substitute(x))) par.model[['x']] <- CheckMaths(x, subst, TRUE) model <- methods::new('RMmodel', call = cl, name = 'R.floor', submodels = submodels, par.model = par.model, par.general = par.general) return(model) } R.floor <- new(CLASS_RM, .Data = R.floor, type = c('shape function', 'trend'), isotropy = c('framework dependent', 'framework dependent'), domain = c('single variable'), operator = FALSE, monotone = 'not monotone', finiterange = FALSE, simpleArguments = TRUE, maxdim = -2, vdim = 1 ) R.fmod <- function(x, y) { cl <- match.call() submodels <- par.general <- par.model <- list() if (hasArg('x') && !is.null(subst <- substitute(x))) par.model[['x']] <- CheckMaths(x, subst, TRUE) if (hasArg('y') && !is.null(subst <- substitute(y))) par.model[['y']] <- CheckMaths(y, subst, TRUE) model <- methods::new('RMmodel', call = cl, name = 'R.fmod', submodels = submodels, par.model = par.model, par.general = par.general) return(model) } R.fmod <- new(CLASS_RM, .Data = R.fmod, type = c('shape function', 'trend'), isotropy = c('framework dependent', 'framework dependent'), domain = c('single variable'), operator = FALSE, monotone = 'not monotone', finiterange = FALSE, simpleArguments = TRUE, maxdim = -2, vdim = 1 ) R.round <- function(x) { cl <- match.call() submodels <- par.general <- par.model <- list() if (hasArg('x') && !is.null(subst <- substitute(x))) par.model[['x']] <- CheckMaths(x, subst, TRUE) model <- methods::new('RMmodel', call = cl, name = 'R.round', submodels = submodels, par.model = par.model, par.general = par.general) return(model) } R.round <- new(CLASS_RM, .Data = R.round, type = c('shape function', 'trend'), isotropy = c('framework dependent', 'framework dependent'), domain = c('single variable'), operator = FALSE, monotone = 'not monotone', finiterange = FALSE, simpleArguments = TRUE, maxdim = -2, vdim = 1 ) R.trunc <- function(x) { cl <- match.call() submodels <- par.general <- par.model <- list() if (hasArg('x') && !is.null(subst <- substitute(x))) par.model[['x']] <- CheckMaths(x, subst, TRUE) model <- methods::new('RMmodel', call = cl, name = 'R.trunc', submodels = submodels, par.model = par.model, par.general = par.general) return(model) } R.trunc <- new(CLASS_RM, .Data = R.trunc, type = c('shape function', 'trend'), isotropy = c('framework dependent', 'framework dependent'), domain = c('single variable'), operator = FALSE, monotone = 'not monotone', finiterange = FALSE, simpleArguments = TRUE, maxdim = -2, vdim = 1 ) R.erfc <- function(x) { cl <- match.call() submodels <- par.general <- par.model <- list() if (hasArg('x') && !is.null(subst <- substitute(x))) par.model[['x']] <- CheckMaths(x, subst, TRUE) model <- methods::new('RMmodel', call = cl, name = 'R.erfc', submodels = submodels, par.model = par.model, par.general = par.general) return(model) } R.erfc <- new(CLASS_RM, .Data = R.erfc, type = c('shape function', 'trend'), isotropy = c('framework dependent', 'framework dependent'), domain = c('single variable'), operator = FALSE, monotone = 'not monotone', finiterange = FALSE, simpleArguments = TRUE, maxdim = -2, vdim = 1 ) R.lgamma <- function(x) { cl <- match.call() submodels <- par.general <- par.model <- list() if (hasArg('x') && !is.null(subst <- substitute(x))) par.model[['x']] <- CheckMaths(x, subst, TRUE) model <- methods::new('RMmodel', call = cl, name = 'R.lgamma', submodels = submodels, par.model = par.model, par.general = par.general) return(model) } R.lgamma <- new(CLASS_RM, .Data = R.lgamma, type = c('shape function', 'trend'), isotropy = c('framework dependent', 'framework dependent'), domain = c('single variable'), operator = FALSE, monotone = 'not monotone', finiterange = FALSE, simpleArguments = TRUE, maxdim = -2, vdim = 1 ) R.remainder <- function(x, y) { cl <- match.call() submodels <- par.general <- par.model <- list() if (hasArg('x') && !is.null(subst <- substitute(x))) par.model[['x']] <- CheckMaths(x, subst, TRUE) if (hasArg('y') && !is.null(subst <- substitute(y))) par.model[['y']] <- CheckMaths(y, subst, TRUE) model <- methods::new('RMmodel', call = cl, name = 'R.remainder', submodels = submodels, par.model = par.model, par.general = par.general) return(model) } R.remainder <- new(CLASS_RM, .Data = R.remainder, type = c('shape function', 'trend'), isotropy = c('framework dependent', 'framework dependent'), domain = c('single variable'), operator = FALSE, monotone = 'not monotone', finiterange = FALSE, simpleArguments = TRUE, maxdim = -2, vdim = 1 ) R.fdim <- function(x, y) { cl <- match.call() submodels <- par.general <- par.model <- list() if (hasArg('x') && !is.null(subst <- substitute(x))) par.model[['x']] <- CheckMaths(x, subst, TRUE) if (hasArg('y') && !is.null(subst <- substitute(y))) par.model[['y']] <- CheckMaths(y, subst, TRUE) model <- methods::new('RMmodel', call = cl, name = 'R.fdim', submodels = submodels, par.model = par.model, par.general = par.general) return(model) } R.fdim <- new(CLASS_RM, .Data = R.fdim, type = c('shape function', 'trend'), isotropy = c('framework dependent', 'framework dependent'), domain = c('single variable'), operator = FALSE, monotone = 'not monotone', finiterange = FALSE, simpleArguments = TRUE, maxdim = -2, vdim = 1 ) R.fmax <- function(x, y) { cl <- match.call() submodels <- par.general <- par.model <- list() if (hasArg('x') && !is.null(subst <- substitute(x))) par.model[['x']] <- CheckMaths(x, subst, TRUE) if (hasArg('y') && !is.null(subst <- substitute(y))) par.model[['y']] <- CheckMaths(y, subst, TRUE) model <- methods::new('RMmodel', call = cl, name = 'R.fmax', submodels = submodels, par.model = par.model, par.general = par.general) return(model) } R.fmax <- new(CLASS_RM, .Data = R.fmax, type = c('shape function', 'trend'), isotropy = c('framework dependent', 'framework dependent'), domain = c('single variable'), operator = FALSE, monotone = 'not monotone', finiterange = FALSE, simpleArguments = TRUE, maxdim = -2, vdim = 1 ) R.fmin <- function(x, y) { cl <- match.call() submodels <- par.general <- par.model <- list() if (hasArg('x') && !is.null(subst <- substitute(x))) par.model[['x']] <- CheckMaths(x, subst, TRUE) if (hasArg('y') && !is.null(subst <- substitute(y))) par.model[['y']] <- CheckMaths(y, subst, TRUE) model <- methods::new('RMmodel', call = cl, name = 'R.fmin', submodels = submodels, par.model = par.model, par.general = par.general) return(model) } R.fmin <- new(CLASS_RM, .Data = R.fmin, type = c('shape function', 'trend'), isotropy = c('framework dependent', 'framework dependent'), domain = c('single variable'), operator = FALSE, monotone = 'not monotone', finiterange = FALSE, simpleArguments = TRUE, maxdim = -2, vdim = 1 ) R.gamma <- function(x) { cl <- match.call() submodels <- par.general <- par.model <- list() if (hasArg('x') && !is.null(subst <- substitute(x))) par.model[['x']] <- CheckMaths(x, subst, FALSE) model <- methods::new('RMmodel', call = cl, name = 'R.gamma', submodels = submodels, par.model = par.model, par.general = par.general) return(model) } R.gamma <- new(CLASS_RM, .Data = R.gamma, type = c('mathematical operator', 'trend'), isotropy = c('framework dependent', 'framework dependent'), domain = c('single variable'), operator = FALSE, monotone = 'not monotone', finiterange = FALSE, simpleArguments = TRUE, maxdim = -2, vdim = 1 ) R.exp <- function(x) { cl <- match.call() submodels <- par.general <- par.model <- list() if (hasArg('x') && !is.null(subst <- substitute(x))) par.model[['x']] <- CheckMaths(x, subst, FALSE) model <- methods::new('RMmodel', call = cl, name = 'R.exp', submodels = submodels, par.model = par.model, par.general = par.general) return(model) } R.exp <- new(CLASS_RM, .Data = R.exp, type = c('mathematical operator', 'trend'), isotropy = c('framework dependent', 'framework dependent'), domain = c('single variable'), operator = FALSE, monotone = 'not monotone', finiterange = FALSE, simpleArguments = TRUE, maxdim = -2, vdim = 1 ) R.erf <- function(x) { cl <- match.call() submodels <- par.general <- par.model <- list() if (hasArg('x') && !is.null(subst <- substitute(x))) par.model[['x']] <- CheckMaths(x, subst, FALSE) model <- methods::new('RMmodel', call = cl, name = 'R.erf', submodels = submodels, par.model = par.model, par.general = par.general) return(model) } R.erf <- new(CLASS_RM, .Data = R.erf, type = c('mathematical operator', 'trend'), isotropy = c('framework dependent', 'framework dependent'), domain = c('single variable'), operator = FALSE, monotone = 'not monotone', finiterange = FALSE, simpleArguments = TRUE, maxdim = -2, vdim = 1 ) R.fabs <- function(x) { cl <- match.call() submodels <- par.general <- par.model <- list() if (hasArg('x') && !is.null(subst <- substitute(x))) par.model[['x']] <- CheckMaths(x, subst, FALSE) model <- methods::new('RMmodel', call = cl, name = 'R.fabs', submodels = submodels, par.model = par.model, par.general = par.general) return(model) } R.fabs <- new(CLASS_RM, .Data = R.fabs, type = c('mathematical operator', 'trend'), isotropy = c('framework dependent', 'framework dependent'), domain = c('single variable'), operator = FALSE, monotone = 'not monotone', finiterange = FALSE, simpleArguments = TRUE, maxdim = -2, vdim = 1 ) R.acos <- function(x) { cl <- match.call() submodels <- par.general <- par.model <- list() if (hasArg('x') && !is.null(subst <- substitute(x))) par.model[['x']] <- CheckMaths(x, subst, FALSE) model <- methods::new('RMmodel', call = cl, name = 'R.acos', submodels = submodels, par.model = par.model, par.general = par.general) return(model) } R.acos <- new(CLASS_RM, .Data = R.acos, type = c('mathematical operator', 'trend'), isotropy = c('framework dependent', 'framework dependent'), domain = c('single variable'), operator = FALSE, monotone = 'not monotone', finiterange = FALSE, simpleArguments = TRUE, maxdim = -2, vdim = 1 ) R.acosh <- function(x) { cl <- match.call() submodels <- par.general <- par.model <- list() if (hasArg('x') && !is.null(subst <- substitute(x))) par.model[['x']] <- CheckMaths(x, subst, FALSE) model <- methods::new('RMmodel', call = cl, name = 'R.acosh', submodels = submodels, par.model = par.model, par.general = par.general) return(model) } R.acosh <- new(CLASS_RM, .Data = R.acosh, type = c('mathematical operator', 'trend'), isotropy = c('framework dependent', 'framework dependent'), domain = c('single variable'), operator = FALSE, monotone = 'not monotone', finiterange = FALSE, simpleArguments = TRUE, maxdim = -2, vdim = 1 ) R.pow <- function(x, y) { cl <- match.call() submodels <- par.general <- par.model <- list() if (hasArg('x') && !is.null(subst <- substitute(x))) par.model[['x']] <- CheckMaths(x, subst, FALSE) if (hasArg('y') && !is.null(subst <- substitute(y))) par.model[['y']] <- CheckMaths(y, subst, FALSE) model <- methods::new('RMmodel', call = cl, name = 'R.pow', submodels = submodels, par.model = par.model, par.general = par.general) return(model) } R.pow <- new(CLASS_RM, .Data = R.pow, type = c('mathematical operator', 'trend'), isotropy = c('framework dependent', 'framework dependent'), domain = c('single variable'), operator = FALSE, monotone = 'not monotone', finiterange = FALSE, simpleArguments = TRUE, maxdim = -2, vdim = 1 ) R.sqrt <- function(x) { cl <- match.call() submodels <- par.general <- par.model <- list() if (hasArg('x') && !is.null(subst <- substitute(x))) par.model[['x']] <- CheckMaths(x, subst, FALSE) model <- methods::new('RMmodel', call = cl, name = 'R.sqrt', submodels = submodels, par.model = par.model, par.general = par.general) return(model) } R.sqrt <- new(CLASS_RM, .Data = R.sqrt, type = c('mathematical operator', 'trend'), isotropy = c('framework dependent', 'framework dependent'), domain = c('single variable'), operator = FALSE, monotone = 'not monotone', finiterange = FALSE, simpleArguments = TRUE, maxdim = -2, vdim = 1 )