npetraco/fdrID: Computes local false discovery rate probabilities using JAGS, Stan and code from Efron, Turnbull and Narasimhan locfdr

Using ideas from Ann. Stat. 35(4):1351-1377 (2007), and some handy code from the former locfdr package, this package computes local false discovery rate (i.e. posterior error probability) estimates for classification/ discrimination tasks using a Bayesian Poission regression. Specifically, the Bayesian Poission regression is used to estimate the denominator of Bayes Theorem within Efron's two-groups empirical Bayes methodology. The regression is a heirarical model and carried out with either JAGS (mcmc-jags.sourceforge.net) or Stan (mc-stan.org), via their R interfaces.

install.packages("remotes")
remotes::install_github("npetraco/fdrID")