CRAN/E | baygel

baygel

Bayesian Shrinkage Estimators for Precision Matrices in Gaussian Graphical Models

Installation

About

This R package offers block Gibbs samplers for the Bayesian (adaptive) graphical lasso, ridge, and naive elastic net priors. These samplers facilitate the simulation of the posterior distribution of precision matrices for Gaussian distributed data and were originally proposed by: Wang (2012) doi:10.1214/12-BA729; Smith et al. (2022) doi:10.48550/arXiv.2210.16290 and Smith et al. (2023) doi:10.48550/arXiv.2306.14199, respectively.

github.com/Jarod-Smithy/baygel

Key Metrics

Version 0.3.0
Published 2023-11-11 161 days ago
Needs compilation? yes
License GPL (≥ 3)
CRAN checks baygel results

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Maintainer

Maintainer

Jarod Smith

jarodsmith706@gmail.com

Authors

Jarod Smith

aut / cre

Mohammad Arashi

aut

Andriette Bekker

aut

Material

Reference manual
Package source

macOS

r-release

arm64

r-oldrel

arm64

r-release

x86_64

r-oldrel

x86_64

Windows

r-devel

x86_64

r-release

x86_64

r-oldrel

x86_64

Old Sources

baygel archive

Imports

Rcpp ≥ 1.0.8
RcppArmadillo ≥ 0.11.1.1.0

Suggests

MASS
pracma

LinkingTo

Rcpp
RcppArmadillo
RcppProgress