_            _    _        _         _
      /\ \         /\ \ /\ \     /\_\      / /\
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      /\__ \     / /\ \ \\ \ \_/ / /     / / /\ \__
     / /_ \ \   / / /\ \ \\ \___/ /     / / /\ \___\
    / / /\ \ \ / / /  \ \_\\ \ \_/      \ \ \ \/___/
   / / /  \/_// / /   / / / \ \ \        \ \ \
  / / /      / / /   / / /   \ \ \   _    \ \ \
 / / /      / / /___/ / /     \ \ \ /_/\__/ / /
/_/ /      / / /____\/ /       \ \_\\ \/___/ /
\_\/       \/_________/         \/_/ \_____\/
r-bamlss 1.2-5
Propagated dependencies: r-survival@3.7-0 r-sp@2.1-4 r-mvtnorm@1.3-2 r-mgcv@1.9-1 r-mba@0.1-2 r-matrix@1.7-1 r-formula@1.2-5 r-distributions3@0.2.2 r-colorspace@2.1-1 r-coda@0.19-4.1
Channel: guix-cran
Location: guix-cran/packages/b.scm (guix-cran packages b)
Home page: http://www.bamlss.org/
Licenses: GPL 2 GPL 3
Synopsis: Bayesian Additive Models for Location, Scale, and Shape (and Beyond)
Description:

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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