lrgs: Linear Regression by Gibbs Sampling

Implements a Gibbs sampler to do linear regression with multiple covariates, multiple responses, Gaussian measurement errors on covariates and responses, Gaussian intrinsic scatter, and a covariate prior distribution which is given by either a Gaussian mixture of specified size or a Dirichlet process with a Gaussian base distribution. Described further in Mantz (2016) <doi:10.1093/mnras/stv3008>.

Version: 0.5.4
Imports: mvtnorm
Published: 2020-08-11
Author: Adam Mantz
Maintainer: Adam Mantz <amantz at slac.stanford.edu>
License: MIT + file LICENSE
URL: https://github.com/abmantz/lrgs
NeedsCompilation: no
CRAN checks: lrgs results

Documentation:

Reference manual: lrgs.pdf

Downloads:

Package source: lrgs_0.5.4.tar.gz
Windows binaries: r-devel: lrgs_0.5.4.zip, r-release: lrgs_0.5.4.zip, r-oldrel: lrgs_0.5.4.zip
macOS binaries: r-release (arm64): lrgs_0.5.4.tgz, r-oldrel (arm64): lrgs_0.5.4.tgz, r-release (x86_64): lrgs_0.5.4.tgz, r-oldrel (x86_64): lrgs_0.5.4.tgz
Old sources: lrgs archive

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