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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