doi:10.1080/10618600.2017.1407325> and the R package in Umlauf, Klein, Simon, Zeileis (2021) <doi:10.18637/jss.v100.i04>.">

bamlss: Bayesian Additive Models for Location, Scale, and Shape (and Beyond) (original) (raw)

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 ORCID iD [aut, cre], Nadja Klein ORCID iD [aut], Achim Zeileis ORCID iD [aut], Meike Koehler [ctb], Thorsten Simon ORCID iD [aut], Stanislaus Stadlmann [ctb], Alexander VolkmannORCID iD [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

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