lrgs: Linear Regression by Gibbs Sampling (original) (raw)
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 |
| DOI: | 10.32614/CRAN.package.lrgs |
| Author: | Adam Mantz |
| Maintainer: | Adam Mantz |
| License: | MIT + file |
| URL: | https://github.com/abmantz/lrgs |
| NeedsCompilation: | no |
| CRAN checks: | lrgs results |
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