FDR Based Multiple Testing Procedures with Adaptation for Discrete Tests
Wrapper Functions for the Adaptive Discrete Benjamini-Hochberg Procedu...
Wrapper Functions for the Discrete Benjamini-Hochberg Procedure
The Discrete Blanchard-Roquain Procedure
Direct Application of Multiple Testing Procedures to Dataset
The Discrete Benjamini-Hochberg Procedure
FDR-based Multiple Testing Procedures with Adaptation for Discrete Tes...
Fast Application of Discrete Multiple Testing Procedures
Computing Discrete P-Values and Their Supports for Fisher's Exact Test
Generation of P-Values and Their Supports After Data Transformations
Histogram of Raw P-Values
Kernel Functions
Matching Raw P-Values with Supports
Plot Method for DiscreteFDR objects
Printing DiscreteFDR results
Summarizing Discrete FDR Results
Implementations of the multiple testing procedures for discrete tests described in the paper Döhler, Durand and Roquain (2018) "New FDR bounds for discrete and heterogeneous tests" <doi:10.1214/18-EJS1441>. The main procedures of the paper (HSU and HSD), their adaptive counterparts (AHSU and AHSD), and the HBR variant are available and are coded to take as input the results of a test procedure from package 'DiscreteTests', or a set of observed p-values and their discrete support under their nulls. A shortcut function to obtain such p-values and supports is also provided, along with a wrapper allowing to apply discrete procedures directly to data.