r-cran-brms 2.20.1-1 source package in Ubuntu

Changelog

r-cran-brms (2.20.1-1) unstable; urgency=medium

  * New upstream version

 -- Andreas Tille <email address hidden>  Fri, 18 Aug 2023 14:21:43 +0200

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Uploaded by:
Debian R Packages Maintainers
Uploaded to:
Sid
Original maintainer:
Debian R Packages Maintainers
Architectures:
all
Section:
misc
Urgency:
Medium Urgency

See full publishing history Publishing

Series Pocket Published Component Section

Builds

Noble: [FULLYBUILT] amd64

Downloads

File Size SHA-256 Checksum
r-cran-brms_2.20.1-1.dsc 2.7 KiB 227656f818d7d2ef1bc992eee9239c7e5923d4122abdd743ef700211da6aa17d
r-cran-brms_2.20.1.orig.tar.gz 4.4 MiB 4908334731f6bd9020e394d68742c3a3558676cc056b04ae4d6bbbb942171e5c
r-cran-brms_2.20.1-1.debian.tar.xz 3.7 KiB 98277ff29c5d55cfe50197294548146b71ccf6c0eb816288c8acd0abbe06d8d4

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Binary packages built by this source

r-cran-brms: GNU R Bayesian regression models using 'Stan'

 Fit Bayesian generalized (non-)linear multivariate multilevel models
 using 'Stan' for full Bayesian inference. A wide range of distributions
 and link functions are supported, allowing users to fit -- among others
  -- linear, robust linear, count data, survival, response times, ordinal,
 zero-inflated, hurdle, and even self-defined mixture models all in a
 multilevel context. Further modeling options include non-linear and
 smooth terms, auto-correlation structures, censored data, meta-analytic
 standard errors, and quite a few more. In addition, all parameters of
 the response distribution can be predicted in order to perform
 distributional regression. Prior specifications are flexible and
 explicitly encourage users to apply prior distributions that actually
 reflect their beliefs. Model fit can easily be assessed and compared
 with posterior predictive checks and leave-one-out cross-validation.