Statistics, Department of

 

The R Journal

Date of this Version

12-2014

Document Type

Article

Citation

The R Journal (December 2014) 6(2); Editor: Deepayan Sarkar

Comments

Copyright 2014, The R Foundation. Open access material. License: CC BY 3.0 Unported

Abstract

In this paper we present a new R package called sgof for multiple hypothesis testing. The principal aim of this package is to implement SGoF-type multiple testing methods, known to be more powerful than the classical false discovery rate (FDR) and family-wise error rate (FWER) based methods in certain situations, particularly when the number of tests is large. This package includes Bi nomial and Conservative SGoF and the Bayesian and Beta-Binomial SGoF multiple testing procedures, which are adaptations of the original SGoF method to the Bayesian setting and to possibly correlated tests, respectively. The sgof package also implements the Benjamini-Hochberg and Benjamini-Yekutieli FDRcontrolling procedures. For each method the package provides (among other things) the number of rejected null hypotheses, estimation of the corresponding FDR, and the set of adjusted p values. Some automatic plots of interest are implemented too. Two real data examples are used to illustrate how sgof works

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