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 (2017) <doi:10.1080/10618600.2017.1407325>.

Package details

AuthorNikolaus Umlauf [aut, cre], Nadja Klein [aut], Achim Zeileis [aut] (<>), Meike Koehler [aut], Thorsten Simon [ctb], Stanislaus Stadlmann [ctb]
MaintainerNikolaus Umlauf <[email protected]>
LicenseGPL-2 | GPL-3
Package repositoryView on CRAN
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bamlss documentation built on May 2, 2019, 8:50 a.m.