himelmallick/UBeRr: Unified Bayesian Regularization via Scale Mixture of Uniform Distributions

UBeRr provides Bayesian regularization methods for high-dimensional linear regression. The methods implemented in this package leverage a novel data augmentation scheme based on the scale mixture of uniform (SMU) distribution that leads to a set of efficient Gibbs samplers with tractable full conditional posterior distributions and superior performance over existing methods.

Getting started

Package details

AuthorHimel Mallick <[email protected]>
MaintainerHimel Mallick <[email protected]>
LicenseMIT
Version0.1
Package repositoryView on GitHub
Installation Install the latest version of this package by entering the following in R:
install.packages("remotes")
remotes::install_github("himelmallick/UBeRr")
himelmallick/UBeRr documentation built on May 6, 2019, 8:07 p.m.