STAREG: An Empirical Bayes Approach for Replicability Analysis Across Two Studies

A robust and powerful empirical Bayesian approach is developed for replicability analysis of two large-scale experimental studies. The method controls the false discovery rate by using the joint local false discovery rate based on the replicability null as the test statistic. An EM algorithm combined with a shape constraint nonparametric method is used to estimate unknown parameters and functions. [Li, Y. et al., (2023), <>].

Version: 1.0.3
Depends: Rcpp (≥ 1.0.9), qvalue
LinkingTo: Rcpp, RcppArmadillo
Published: 2023-08-15
DOI: 10.32614/CRAN.package.STAREG
Author: Yan Li [aut, cre, cph], Xiang Zhou [aut], Rui Chen [aut], Xianyang Zhang [aut], Hongyuan Cao [aut, ctb]
Maintainer: Yan Li <yanli_ at>
License: GPL-3
NeedsCompilation: yes
CRAN checks: STAREG results


Reference manual: STAREG.pdf


Package source: STAREG_1.0.3.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release (arm64): STAREG_1.0.3.tgz, r-oldrel (arm64): STAREG_1.0.3.tgz, r-release (x86_64): STAREG_1.0.3.tgz, r-oldrel (x86_64): STAREG_1.0.3.tgz
Old sources: STAREG archive


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