PositiveDeptCF: Critical Function for Hierarchical FDR Controlling Procedure...

In allenzhuaz/MHThier: Multiple Hypotheses Testing for Hierarchical Data

Description

Given some parameters of the descendant hypotheses, return the critical function using the generalized hierarchical FDR controlling procedure under positive dependence (see Theorem 1 in Lynch et al. (2016)).

Usage

PositiveDeptCF(isTested, mi, li, l, alpha, rOffset)

Arguments

isTested	logical; if TRUE (default), then the i-th hypotheses H_i will be tested; otherwise, H_i will not be tested.
mi	the cardinality of the set of descendant hypotheses H_i.
li	the number of leaf hypotheses in the set of descendant hypotheses H_i.
l	the total number of leaf hypotheses.
alpha	the significant level used to calculate the critical values to make decisions.
rOffset	the offset increment for the number of rejections.

Value

A critical function of the index i and rejection number R.

Author(s)

Yalin Zhu

References

Lynch, G., Guo, W. (2016). On Procedures Controlling the FDR for Testing Hierarchically Ordered Hypotheses. arXiv preprint arXiv:1612.04467.

allenzhuaz/MHThier documentation built on May 6, 2019, 1:30 a.m.