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bamlss: Bayesian Additive Models for Location, Scale, and Shape (and Beyond)
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>.
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Package details |
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| Author | Nikolaus Umlauf [aut, cre] (<https://orcid.org/0000-0003-2160-9803>), Nadja Klein [aut] (<https://orcid.org/0000-0002-5072-5347>), 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], Alexander Volkmann [ctb] (<https://orcid.org/0000-0001-5028-8098>) |
| Maintainer | Nikolaus Umlauf <Nikolaus.Umlauf@uibk.ac.at> |
| License | GPL-2 | GPL-3 |
| Version | 1.2-3 |
| URL | http://www.bamlss.org/ |
| Package repository | View on R-Forge |
| Installation |
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