MMVBVS: Missing Multivariate Bayesian Variable Selection

A variable selection tool for multivariate normal variables with missing-at-random values using Bayesian Hierarchical Model. Visualization functions show the posterior distribution of gamma (inclusion variables) and beta (coefficients). Users can also visualize the heatmap of the posterior mean of covariance matrix. Kim, T. Nicolae, D. (2019) <https://github.com/tk382/MMVBVS/blob/master/workingpaper.pdf>. Guan, Y. Stephens, M. (2011) <doi:10.1214/11-AOAS455>.

Getting started

Package details

AuthorTae Kim
MaintainerTae Kim <tk382@uchicago.edu>
LicenseGPL (>= 2)
Version0.8.0
Package repositoryView on CRAN
Installation Install the latest version of this package by entering the following in R:
install.packages("MMVBVS")

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MMVBVS documentation built on Dec. 16, 2019, 1:33 a.m.