Mulpval: Multiple hypothesis tests for p values

In equSA: Learning High-Dimensional Graphical Models

Description

Conduct multiple hypothesis tests from p values.

Usage

Mulpval(pvalue, ALPHA2=0.05,GRID=2,iteration=100)

Arguments

pvalue	A vector of p values.
ALPHA2	The significance level of screening, default of 0.05.
GRID	The number of components for the z-scores. The default value is 2.
iteration	Number of iterations for screening. The default value is 100.

Details

This is the function that conduct multiple hypothesis test for p values.

Value

qqqscore

The threshold of p value which indicates that p values are not larger than the threshold are considered significance and larger otherwise.

Author(s)

Bochao Jia, Faming [e-mail]

References

Liang, F. and Zhang, J. (2008) Estimating FDR under general dependence using stochastic approximation. Biometrika, 95(4), 961-977.

Examples

library(equSA)
pvalue <- c(runif(20,0,0.001),runif(200,0,1))
Mulpval(pvalue,ALPHA2=0.05)

equSA documentation built on May 6, 2019, 1:06 a.m.