Efficient Sampling for Gaussian Linear Regression with Arbitrary Priors

Efficient sampling for Gaussian linear regression with arbitrary priors, Hahn, He and Hedibert (2018) .


Description

Efficient sampling for Gaussian linear regression with arbitrary priors. This package implements Bayesian linear regression using elliptical slice sampler, which allows easily useage of arbitrary priors. This package is parallelized by RcppParallel.

Install

install.packages("devtools")

library(devtools)

install_github("JingyuHe/bayeslm")

Reference

Hahn, P. Richard, Jingyu He, and Hedibert Lopes. " Efficient sampling for Gaussian linear regression with arbitrary priors." (2017).

bayeslm

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Reference manual

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install.packages("bayeslm")

0.8.0 by Jingyu He, 7 months ago


http://jingyuhe.com/software.html


Browse source code at https://github.com/cran/bayeslm


Authors: P. Richard Hahn , Jingyu He , Hedibert Lopes


Documentation:   PDF Manual  


LGPL (>= 2) license


Imports Rcpp, stats, graphics, grDevices, coda, RcppParallel

Linking to Rcpp, RcppArmadillo, RcppParallel

System requirements: GNU make


See at CRAN