This package is considered a duplicate. The official version of this package is found at:https://stephenslab.r-universe.dev/mr.mashr

Package: mr.mashr 0.3.44

Peter Carbonetto

mr.mashr: Multiple Regression with Multivariate Adaptive Shrinkage

Provides an implementation of methods for multivariate multiple regression with adaptive shrinkage priors as described in F. Morgante et al (2023) <doi:10.1371/journal.pgen.1010539>.

Authors:Fabio Morgante [aut], Jason Willwerscheid [ctb], Gao Wang [ctb], Deborah Kunkel [aut], Daniel Nachun [ctb], Peter Carbonetto [cre, aut], Matthew Stephens [aut]

mr.mashr_0.3.44.tar.gz
mr.mashr_0.3.44.tar.gz(r-4.7-arm64)mr.mashr_0.3.44.tar.gz(r-4.7-x86_64)mr.mashr_0.3.44.tar.gz(r-4.6-arm64)mr.mashr_0.3.44.tar.gz(r-4.6-x86_64)
manual.pdf |manual.html✨
card.svg |card.png
mr.mashr/json (API)

# Install 'mr.mashr' in R:

install.packages('mr.mashr', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/stephenslab/mr.mashr/issues

Uses libs:

openblas– Optimized BLAS
c++– GNU Standard C++ Library v3

On CRAN:

openblas cpp

2.70 score 3 scripts 447 downloads 12 exports 54 dependencies

Last updated from:6bd3f33a12. Checks:5 OK, 1 FAIL. Indexed: no.

Target	Result	Time
linux-devel-arm64	OK	245
linux-devel-x86_64	OK	263
source / vignettes	OK	404
linux-release-arm64	OK	259
linux-release-x86_64	OK	255
wasm-release	FAIL	123

Exports:autoselect.mixsd coef.mr.mash coef.mr.mash.rss compute_canonical_covs compute_data_driven_covs compute_univariate_sumstats expand_covs mr.mash mr.mash.rss predict.mr.mash predict.mr.mash.rss simulate_mr_mash_data

Dependencies:abind ashr assertthat cli cpp11 deconvolveR dplyr ebnm etrunct farver flashier generics ggplot2 glue gtable invgamma irlba isoband labeling lattice lifecycle magrittr mashr Matrix matrixStats mixsqp mvtnorm pillar pkgconfig plyr purrr R6 RColorBrewer Rcpp RcppArmadillo RcppGSL RcppParallel rlang rmeta S7 scales softImpute SQUAREM stringi stringr tibble tidyr tidyselect truncnorm trust utf8 vctrs viridisLite withr

Introduction to mr.mash

Peter Carbonetto & Fabio Morgante

Rendered frommr_mash_intro.Rmdusingknitr::rmarkdownon Jun 06 2026.

Last update: 2026-01-07
Started: 2026-01-07

Citation

Readme and manuals

Help Manual

Help page	Topics
Compute a grid of standard deviations to scale the canonical covariance matrices.	autoselect.mixsd
Extract coefficients from mr.mash fit.	coef.mr.mash
Extract coefficients from mr.mash.rss fit.	coef.mr.mash.rss
Compute canonical covariance matrices.	compute_canonical_covs
Compute data-driven covariance matrices.	compute_data_driven_covs
Compute summary statistics from univariate simple linear regression.	compute_univariate_sumstats
Expand covariance matrices by a grid of variances for use in 'mr.mash'.	expand_covs
Multiple Regression with Multivariate Adaptive Shrinkage.	mr.mash
Multiple Regression with Multivariate Adaptive Shrinkage from summary data.	mr.mash.rss
Predict future observations from mr.mash fit.	predict.mr.mash
Predict future observations from mr.mash.rss fit.	predict.mr.mash.rss
Simulate data to test 'mr.mash'.	simulate_mr_mash_data