Crandore Hub

mashr

Multivariate Adaptive Shrinkage

Implements the multivariate adaptive shrinkage (mash) method of Urbut et al (2019) <DOI:10.1038/s41588-018-0268-8> for estimating and testing large numbers of effects in many conditions (or many outcomes). Mash takes an empirical Bayes approach to testing and effect estimation; it estimates patterns of similarity among conditions, then exploits these patterns to improve accuracy of the effect estimates. The core linear algebra is implemented in C++ for fast model fitting and posterior computation.

Versions across snapshots

VersionRepositoryFileSize
0.2.79 rolling linux/jammy R-4.5 mashr_0.2.79.tar.gz 650.2 KiB
0.2.79 rolling linux/noble R-4.5 mashr_0.2.79.tar.gz 659.2 KiB
0.2.79 rolling source/ R- mashr_0.2.79.tar.gz 515.3 KiB
0.2.79 latest linux/jammy R-4.5 mashr_0.2.79.tar.gz 650.2 KiB
0.2.79 latest linux/noble R-4.5 mashr_0.2.79.tar.gz 659.2 KiB
0.2.79 latest source/ R- mashr_0.2.79.tar.gz 515.3 KiB
0.2.79 2026-04-26 source/ R- mashr_0.2.79.tar.gz 515.3 KiB
0.2.79 2026-04-23 source/ R- mashr_0.2.79.tar.gz 515.3 KiB
0.2.79 2026-04-09 windows/windows R-4.5 mashr_0.2.79.zip 1.2 MiB
0.2.79 2025-04-20 source/ R- mashr_0.2.79.tar.gz 515.3 KiB

Dependencies (latest)

Depends

Imports

LinkingTo

Suggests