lrgs-package: Linear Regression by Gibbs Sampling
In lrgs: Linear Regression by Gibbs Sampling
Description
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.
Details
Package: lrgs
Type: Package
Version: 0.5.4
Date: 2018-05-17
License: MIT
LazyLoad: yes
See help for Gibbs.regression
Author(s)
Adam Mantz <amantz@slac.stanford.edu>
lrgs documentation built on Aug. 11, 2020, 5:08 p.m.
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Description
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.
Details
| Package: | lrgs |
| Type: | Package |
| Version: | 0.5.4 |
| Date: | 2018-05-17 |
| License: | MIT |
| LazyLoad: | yes |
See help for Gibbs.regression
Author(s)
Adam Mantz <amantz@slac.stanford.edu>
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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