https://github.com/cran/bamlss
Tip revision: d0c72305873d5697f0d8a1e9798b1b89344740b3 authored by Nikolaus Umlauf on 18 March 2024, 10:00:02 UTC
version 1.2-3
version 1.2-3
Tip revision: d0c7230
NAMESPACE
import("coda")
import("mgcv")
import("Formula")
import("colorspace")
## importFrom("bit", "chunk", "chunk.default")
## importFrom("ff", "chunk.ff_vector", "chunk.ffdf", "chunk.bit", "read.table.ffdf",
## "ff", "ffdf", "fforder", "as.ff", "ffapply", "nrow<-", "hi")
## importFrom("ffbase", "ffappend", "range.ff")
importFrom("parallel", "mclapply")
importFrom("sp", "bbox", "point.in.polygon", "polygons",
"coordinates", "Polygon", "Polygons", "SpatialPolygons", "SpatialPoints",
"CRS", "proj4string", "coordinates<-", "proj4string<-")
importFrom("splines", "splineDesign", "bs")
importFrom("MBA", "mba.points")
importFrom("survival", "Surv")
importFrom("mvtnorm", "rmvnorm", "dmvnorm")
importFrom("stats", "AIC", "BIC", "family")
importFrom("grDevices", "chull", "dev.interactive", "devAskNewPage",
"gray", "gray.colors", "n2mfrow", "trans3d", "rgb", "dev.off", "png")
importFrom("graphics", "abline", "axis", "box", "contour", "hist",
"layout", "lcm", "lines", "matplot", "mtext", "par",
"points", "rect", "text", "plot.default", "barplot", "title", "legend", "grid")
importFrom("methods", "is", "as", "slot")
importFrom("stats", "acf", "as.formula", "coef", "complete.cases",
"contrasts<-", "dbeta", "dbinom", "delete.response",
"density", "dgamma", "dist", "dlnorm", "dlogis", "dnbinom",
"dnorm", "dpois", "drop.terms", "dt", "dweibull", "end",
"fitted", "formula", "gaussian", "integrate", "lm.wfit",
"lowess", "make.link", "model.frame", "model.matrix",
"model.offset", "model.response", "model.weights",
"na.fail", "na.omit", "optim", "optimHess", "optimize",
"pbeta", "pbinom", "pgamma", "plnorm", "plogis", "pnbinom",
"pnorm", "ppois", "predict", "printCoefmat", "pt", "qnorm",
"qqline", "qqnorm", "quantile", "rexp", "rgamma",
"rmultinom", "rnorm", "runif", "rweibull", "sd", "start",
"terms", "terms.formula", "time", "uniroot", "update",
"var", "window", "median", "asOneSidedFormula", "ecdf",
"pweibull", "qlogis", "rbeta", "rbinom", "rlnorm", "rpois",
"qgamma", "qlnorm", "qweibull", "prcomp", "deviance", "cor",
"lm.fit", "nls.control", "qbeta", "qbinom", "qpois", "na.pass", "relevel",
".getXlevels", "binomial", "glm", "glm.fit", "lm", "naresid", "residuals",
"weights", "kmeans", "setNames")
importFrom("utils", "download.file", "flush.console", "getS3method",
"head", "read.csv2", "read.table", "tail", "unzip",
"write.table", "combn", "capture.output", "getFromNamespace")
import("Matrix")
export(
## main user interface
"bamlss",
"bamlss.frame",
"bamlss.formula",
"bamlss.family",
"opt_bfit",
"opt_bbfit",
"opt_bbfitp",
"bfit",
"bbfit",
"bbfitp",
"contribplot",
"bfit_iwls",
"bfit_iwls_Matrix",
"bfit_lm",
"bfit_optim",
"bfit_glmnet",
"sam_GMCMC",
"GMCMC",
"GMCMC_iwls",
"GMCMC_iwlsC",
"GMCMC_iwlsC_gp",
"GMCMC_slice",
"sam_JAGS",
"sam_BayesX",
"JAGS",
"BayesX",
"BayesX.control",
"get_BayesXsrc",
"sam_MVNORM",
"MVNORM",
"surv_transform",
"opt_Cox",
"sam_Cox",
"cox_mode",
"cox_mcmc",
"cox_predict",
## engine setup functions
"randomize",
"trans_random",
"trans_AR1",
"AR1",
"set.starting.values",
"bamlss.engine.setup",
"get.state",
"get.par",
"set.par",
## families,
"ALD_bamlss",
"AR1_bamlss",
"beta_bamlss",
"beta1_bamlss",
"binomial_bamlss",
"cnorm_bamlss",
"cox_bamlss",
"dirichlet_bamlss",
"dw_bamlss",
"ELF_bamlss",
"gaussian_bamlss",
"gaussian2_bamlss",
"Gaussian_bamlss",
"gamma_bamlss",
"logNN_bamlss",
"multinomial_bamlss",
"mvnorm_bamlss",
"poisson_bamlss",
"quant_bamlss",
"gpareto_bamlss",
"glogis_bamlss",
"nbinom_bamlss",
"ztnbinom_bamlss",
"lognormal_bamlss",
"weibull_bamlss",
"gumbel_bamlss",
"gF",
"Sichel_bamlss",
"GEV_bamlss",
"mix_bamlss",
"DGP_bamlss",
"ZANBI_bamlss",
## extractor functions
"DIC",
"samples",
"samplestats",
"results.bamlss.default",
"parameters",
"WAIC",
## vis functions
"plot2d",
"plot3d",
"plotmap",
"plotblock",
"sliceplot",
"colorlegend",
## JM
"jm_bamlss",
"opt_JM",
"sam_JM",
"jm_mcmc",
"jm_mode",
"simJM",
"rJM",
"jm_survplot",
"jm_predict",
## others
"GAMart",
"Volcano",
"Crazy",
"Surv2",
"c95",
"s2",
"sx",
"rSurvTime2",
"simSurv",
"scale2",
"continue",
"homstart_data",
"tx",
"tx2",
"tx3",
"tx4",
"rmf",
"smooth.construct",
"smooth.construct.tensorX.smooth.spec",
"Predict.matrix.tensorX.smooth",
"smooth.construct.tensorX3.smooth.spec",
"Predict.matrix.tensorX3.smooth",
"BUGSeta",
"BUGSmodel",
"neighbormatrix",
"plotneighbors",
"bamlss.model.frame",
## boosting/lasso
"opt_boost",
"opt_boostm",
"boost",
"boostm",
"boost_summary",
"boost_plot",
"boost_frame",
"la",
"opt_lasso",
"lasso",
"lasso_plot",
"lasso_stop",
"lasso_coef",
"lasso_transform",
## neural nets
"n",
"n.weights",
"predictn",
"ddnn",
"predict.ddnn",
"cv_ddnn",
"make_weights",
## linear effects
"lin",
"smooth.construct.linear.smooth.spec",
## random bits
"rb",
"smooth.construct.randombits.smooth.spec",
## monotone P-splines
"smooth.construct.ms.smooth.spec",
## stability selection
"stabsel",
## kriging
"smooth.construct.kr.smooth.spec",
"Predict.matrix.kriging.smooth",
## shortcuts
"boost2",
"lasso2",
"bayesx2",
"bboost",
"predict.bboost",
"bboost_plot",
"pathplot",
## misc
"response_name",
"smooth_check",
"engines",
"gamlss_distributions",
"CRPS",
## mvnchol
"dist_mvnchol",
"make_formula",
"mvn_chol",
"mvn_modchol",
"mvnchol_bamlss"
)
S3method("plot", "bamlss")
S3method("plot", "bnd")
S3method("plot", "bamlss.results")
S3method("plot", "bamlss.residuals")
S3method("c", "bamlss.residuals")
S3method("plot", "bamlss.residuals.list")
S3method("plot", "stabsel")
S3method("summary", "bamlss")
S3method("summary", "stabsel")
S3method("family", "bamlss")
S3method("family", "bamlss.frame")
S3method("family", "stabsel")
S3method("print", "summary.bamlss")
S3method("print", "family.bamlss")
S3method("print", "bamlss.frame")
S3method("print", "bamlss")
S3method("print", "boost_summary")
S3method("print", "bamlss.formula")
S3method("print", "stabsel")
S3method("print", "summary.stabsel")
S3method("plot", "boost_summary")
S3method("predict", "bamlss")
S3method("predict", "boost_frame")
S3method("fitted", "bamlss")
S3method("logLik", "bamlss")
S3method("DIC", "bamlss")
S3method("DIC", "gmcmc")
S3method("coef", "bamlss")
S3method("confint", "bamlss")
S3method("residuals", "bamlss")
S3method("model.matrix", "bamlss.frame")
S3method("model.matrix", "bamlss.terms")
S3method("model.matrix", "bamlss.formula")
S3method("smooth.construct", "bamlss.frame")
S3method("smooth.construct", "bamlss.formula")
S3method("smooth.construct", "bamlss.terms")
S3method("smooth.construct", "kr.smooth.spec")
S3method("smooth.construct", "tensorX.smooth.spec")
S3method("smooth.construct", "tensorX3.smooth.spec")
S3method("smooth.construct", "la.smooth.spec")
S3method("smooth.construct", "nnet.smooth.spec")
S3method("smooth.construct", "nnet2.smooth.spec")
S3method("smooth.construct", "linear.smooth.spec")
S3method("smooth.construct", "randombits.smooth.spec")
S3method("smooth.construct", "sr.smooth.spec")
S3method("smooth.construct", "ms.smooth.spec")
S3method("Predict.matrix", "kriging.smooth")
S3method("Predict.matrix", "deriv.smooth")
S3method("Predict.matrix", "tensorX.smooth")
S3method("Predict.matrix", "tensorX3.smooth")
S3method("Predict.matrix", "lasso.smooth")
S3method("Predict.matrix", "nnet.smooth")
S3method("Predict.matrix", "nnet2.smooth")
S3method("Predict.matrix", "nnet3.smooth")
S3method("Predict.matrix", "linear.smooth")
S3method("Predict.matrix", "randombits.smooth")
S3method("Predict.matrix", "srand.smooth")
S3method("Predict.matrix", "ff_smooth.smooth.spec")
S3method("bamlss.engine.setup.smooth", "default")
S3method("sx.construct", "tensorX.smooth")
S3method("terms", "bamlss")
S3method("terms", "bamlss.frame")
S3method("terms", "bamlss.formula")
S3method("samples", "bamlss")
S3method("samples", "bamlss.frame")
S3method("model.frame", "bamlss")
S3method("model.frame", "bamlss.frame")
S3method("predict", "ddnn")
S3method("predict", "bboost")
S3method("fitted", "ddnn")
S3method("residuals", "ddnn")
S3method("formula", "bamlss.formula.character")
S3method("formula", "bamlss.formula")
S3method("formula", "stabsel")
S3method("as.character", "bamlss.formula")
S3method("as.character", "bamlss.terms")
S3method("prodist", "bamlss")
S3method("smooth.construct", "Re.smooth.spec")
S3method("smooth.construct", "Re2.smooth.spec")
S3method("smooth.construct", "fdl.smooth.spec")
S3method("smooth.construct", "ha.smooth.spec")
S3method("smooth.construct", "ispline.smooth.spec")
S3method("smooth.construct", "mlt.smooth.spec")
S3method("smooth.construct", "nnet0.smooth.spec")
S3method("smooth.construct", "re2.smooth.spec")
S3method("smooth.construct", "rs.smooth.spec")
S3method("smooth.construct", "rsc.smooth.spec")
S3method("smooth.construct", "str.smooth.spec")
## For topmodels.
import("distributions3")
export(BAMLSS)
S3method(cdf, BAMLSS)
S3method(family, BAMLSS)
S3method(format, BAMLSS)
S3method(is_continuous, BAMLSS)
S3method(is_discrete, BAMLSS)
S3method(kurtosis, BAMLSS)
S3method(log_pdf, BAMLSS)
S3method(mean, BAMLSS)
S3method(pdf, BAMLSS)
S3method(print, BAMLSS)
S3method(quantile, BAMLSS)
S3method(random, BAMLSS)
S3method(scoringRules::crps, BAMLSS)
S3method(skewness, BAMLSS)
S3method(support, BAMLSS)
S3method(variance, BAMLSS)
useDynLib(bamlss, .registration = TRUE)