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.
|License||GPL (>= 2)|
|Package repository||View on GitHub|
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