Infrastructure for estimating probabilistic distributional regression models in a Bayesian framework. The distribution parameters may capture location, scale, shape, etc. and every parameter may depend on complex additive terms (fixed, random, smooth, spatial, etc.) similar to a generalized additive model. The conceptual and computational framework is introduced in Umlauf, Klein, Zeileis (2019) <doi:10.1080/10618600.2017.1407325> and the R package in Umlauf, Klein, Simon, Zeileis (2021) <doi:10.18637/jss.v100.i04>.
| Version: | 1.2-5 |
| Depends: | R (≥ 3.5.0),coda,colorspace,distributions3 (≥ 0.2.1),mgcv |
| Imports: | Formula,MBA,mvtnorm,sp,Matrix,survival, methods, parallel |
| Suggests: | bit,ff,fields,gamlss,gamlss.dist,interp,rjags,BayesX,mapdata,maps,sf,nnet,spatstat,spdep,zoo,keras,splines2,sdPrior,statmod,glogis,glmnet,scoringRules,knitr,rmarkdown,MASS,tensorflow |
| Published: | 2024-10-11 |
| DOI: | 10.32614/CRAN.package.bamlss |
| Author: | Nikolaus Umlauf [aut, cre], Nadja Klein [aut], Achim Zeileis [aut], Meike Koehler [ctb], Thorsten Simon [aut], Stanislaus Stadlmann [ctb], Alexander Volkmann [ctb] |
| Maintainer: | Nikolaus Umlauf <Nikolaus.Umlauf at uibk.ac.at> |
| License: | GPL-2 |GPL-3 |
| URL: | http://www.bamlss.org/ |
| NeedsCompilation: | yes |
| Citation: | bamlss citation info |
| Materials: | NEWS |
| In views: | Bayesian,MixedModels |
| CRAN checks: | bamlss results |