\name{RFlinearpart} \alias{RFlinearpart} \title{Linear part of \command{\link{RMmodel}}} \description{ \command{\link{RFlinearpart}} returns the linear part of a model } \usage{ RFlinearpart(model, x, y = NULL, z = NULL, T = NULL, grid, data, distances, dim, set=0, ...) } \arguments{ \item{model}{object of class \code{\link[=RMmodel-class]{RMmodel}}; the covariance or variogram model, which is to be evaluated} \item{x}{vector or \eqn{(n \times \code{dim})}{(n x \code{dim})}-matrix, where \eqn{n} is the number of points at which the covariance function is to be evaluated; in particular, if the model is isotropic or \code{dim=1} then \code{x} is a vector. \code{x}} \item{y}{second vector or matrix for non-stationary covariance functions} \item{z}{z-component of point if xyzT-specification of points is used} \item{T}{T-component of point if xyzT-specification of points is used} \item{grid}{boolean; whether xyzT specify a grid} \item{data}{vector or matrix of values measured at \code{coord}; If a matrix is given then the columns are interpreted as independent realisations.\cr If also a time component is given, then in the data the indices for the spatial components run the fastest. If an \code{m}-variate model is used, then each realisation is given as \code{m} consecutive columns of \code{data}. } \item{distances}{vector; the lower triangular part of the distance matrix column-wise; equivalently the upper triangular part of the distance matrix row-wise; either \code{x} or \code{distances} must be missing} \item{dim}{dimension of the coordinate space in which the model is applied; only necesary for given \code{distances}} \item{set}{integer. See section Value for details.} \item{...}{for advanced further options and control arguments for the simulation that are passed to and processed by \command{\link{RFoptions}} } } \note{ In the linear part of the model specification the parameters that are NA must be the first model part. I.e. \code{NA * sin(R.p(new="isotropic")) + NA + R.p(new="isotropic")} is OK, but not \code{sin(R.p(new="isotropic")) * NA + NA + R.p(new="isotropic")} } \value{ \command{\link{RFlinearpart}} returns a list of three components, \code{Y}, \code{X}, \code{vdim} returning the deterministic trend, the design matrix, and the multivariability, respectively. If \code{set} is positive, \code{Y} and \code{X} contain the values for the \code{set}-th set of coordinates. Else, \code{Y} and \code{X} are both lists containing the values for all the sets. } \author{Martin Schlather, \email{schlather@math.uni-mannheim.de} \url{http://ms.math.uni-mannheim.de/de/publications/software} } \seealso{ \link{Bayesian}, \command{\link{RMmodel}}, \command{\link{RFsimulate}}, \command{\link{RFlikelihood}}. } \examples{ RFoptions(seed=0) ## *ANY* simulation will have the random seed 0; set ## RFoptions(seed=NA) to make them all random again x <- seq(0, pi, len=10) trend <- 2 * sin(R.p(new="isotropic")) + 3 model <- RMexp(var=2, scale=1) + trend print(RFlinearpart(model, x=x)) ## only a deterministic part trend <- NA * sin(R.p(new="isotropic")) + NA + R.p(new="isotropic") / pi model <- RMexp(var=NA, scale=NA) + trend print(RFlinearpart(model, x=x)) \dontshow{FinalizeExample()} } \keyword{spatial}