DiscreteFDR {DiscreteFDR} R Documentation

## DiscreteFDR

### Description

This package implements the [HSU], [HSD], [AHSU], [AHSD] and [HBR-lambda] procedures for discrete tests (see References).

### Details

The functions are reorganized from the reference paper in the following way. discrete.BH (for Discrete Benjamini-Hochberg) implements [HSU], [HSD], [AHSU] and [AHSD] and DBR (for Discrete Blanchard-Roquain) implements [HBR-lambda]. DBH and ADBH are wrappers for discrete.BH to access [HSU] and [HSD], as well as [AHSU] and [AHSD] directly. Their main arguments are a vector of raw observed p-values, and a list of the same length, which elements are the discrete supports of the CDFs of the p-values.

The function fisher.pvalues.support allows to compute such p-values and support in the framework of a Fisher's exact test of association. It has been inspired by an help page of the package discreteMTP.

The function fast.Discrete is a wrapper for fisher.pvalues.support and discrete.BH which allows to apply discrete procedures directly to a data set of contingency tables.

We also provide the amnesia data set, used in our examples and in our paper. It is basically the amnesia data set of package discreteMTP, but slightly reformatted (the difference lies in column 3).

No other function of the package should be used, they are only internal functions called by the main ones.

### References

Döhler, S., Durand, G., & Roquain, E. (2018). New FDR bounds for discrete and heterogeneous tests. Electronic Journal of Statistics, 12(1), 1867-1900. doi: 10.1214/18-EJS1441

### Author(s)

Maintainer: Florian Junge florian.junge@h-da.de

Authors:

• Guillermo Durand [contributor]

Other contributors:

• Sebastian Döhler [contributor]

• Etienne Roquain [contributor]