power.tpm: Statistical power of truncated product method test under...

In TFisher: Optimal Thresholding Fisher's P-Value Combination Method

Description

Statistical power of truncated product method test under Gaussian mixture model.

Usage

power.tpm(alpha, n, tau1, eps = 0, mu = 0)

Arguments

alpha	- type-I error rate.
n	- dimension parameter, i.e. the number of input p-values.
tau1	- truncation parameter. 0 < tau1 <= 1. tau1 > 0.
eps	- mixing parameter of the Gaussian mixture.
mu	- mean of non standard Gaussian model.

Details

We consider the following hypothesis test,

H_0: X_i\sim F_0, H_a: X_i\sim (1-ε)F_0+ε F_1

, where ε is the mixing parameter, F_0 is the standard normal CDF and F = F_1 is the CDF of normal distribution with μ defined by mu and σ = 1.

Value

Power of the truncated product method test.

References

1. Hong Zhang and Zheyang Wu. "TFisher Tests: Optimal and Adaptive Thresholding for Combining p-Values", submitted.

See Also

stat.soft for the definition of the statistic.

Examples

alpha = 0.05
#If the alternative hypothesis Gaussian mixture with eps = 0.1 and mu = 1.2:#
power.tpm(alpha, 100, 0.05, eps = 0.1, mu = 1.2)

TFisher documentation built on May 2, 2019, 12:20 p.m.