c(person(given = "Nikolaus", family = "Umlauf", role = c("aut", "cre"), email = "Nikolaus.Umlauf@uibk.ac.at"),
person(given = "Nadja", family = "Klein", role = "aut", email = "nklein@uni-goettingen.de"),
person(given = "Achim", family = "Zeileis", role = "aut", email = "Achim.Zeileis@R-project.org",
comment = c(ORCID = "0000-0003-0918-3766")),
person(given = "Meike", family = "Koehler", role = "ctb", email = "meike_koehler@gmx.de"),
person(given = "Thorsten", family = "Simon", role = "aut", email = "thorsten.simon@uibk.ac.at",
comment = c(ORCID = "0000-0002-3778-7738")),
person(given = "Stanislaus", family = "Stadlmann", role = "ctb", email = "stadlmann@uni-goettingen.de"))
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 (2018)
<doi:10.1080/10618600.2017.1407325>.
akima, bit, ff, ffbase, fields, gamlss, geoR, rjags, BayesX,
BayesXsrc, mapdata, maps, maptools, raster, spatstat, spdep,
zoo, keras, splines2, sdPrior, glogis, glmnet, scoringRules
Nikolaus Umlauf [aut, cre],
Nadja Klein [aut],
Achim Zeileis [aut] (<https://orcid.org/0000-0003-0918-3766>),
Meike Koehler [ctb],
Thorsten Simon [aut] (<https://orcid.org/0000-0002-3778-7738>),
Stanislaus Stadlmann [ctb]

Bayesian Additive Models for Location, Scale, and Shape (and
Beyond)
c(person(given = "Nikolaus", family = "Umlauf", role = c("aut", "cre"), email = "Nikolaus.Umlauf@uibk.ac.at",
comment = c(ORCID = "0000-0003-2160-9803")),
person(given = "Nadja", family = "Klein", role = "aut", email = "nklein@uni-goettingen.de"),
person(given = "Achim", family = "Zeileis", role = "aut", email = "Achim.Zeileis@R-project.org",
comment = c(ORCID = "0000-0003-0918-3766")),
person(given = "Meike", family = "Koehler", role = "ctb", email = "meike_koehler@gmx.de"),
person(given = "Thorsten", family = "Simon", role = "aut", email = "thorsten.simon@uibk.ac.at",
comment = c(ORCID = "0000-0002-3778-7738")),
person(given = "Stanislaus", family = "Stadlmann", role = "ctb", email = "stadlmann@uni-goettingen.de"))
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 (2019)
<arXiv:1909.11784>.
akima, bit, ff, ffbase, fields, gamlss, geoR, rjags, BayesX,
BayesXsrc, R2BayesX, mapdata, maps, maptools, raster, spatstat,
spdep, zoo, keras, splines2, sdPrior, glogis, glmnet,
scoringRules, knitr, MASS
Nikolaus Umlauf [aut, cre] (<https://orcid.org/0000-0003-2160-9803>),
Nadja Klein [aut],
Achim Zeileis [aut] (<https://orcid.org/0000-0003-0918-3766>),
Meike Koehler [ctb],
Thorsten Simon [aut] (<https://orcid.org/0000-0002-3778-7738>),
Stanislaus Stadlmann [ctb]