| power.tfisher {TFisher} | R Documentation |
Statistical power of thresholding Fisher's p-value combination test under Gaussian mixture model.
Description
Statistical power of thresholding Fisher's p-value combination test under Gaussian mixture model.
Usage
power.tfisher(alpha, n, tau1, tau2, 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. |
tau2 |
- normalization parameter. tau2 >= tau1. |
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-\epsilon)F_0+\epsilon F_1
, where \epsilon is the mixing parameter,
F_0 is the standard normal CDF and F = F_1 is the CDF of normal distribution with \mu defined by mu and \sigma = 1.
Value
Power of the thresholding Fisher's p-value combination test.
References
1. Hong Zhang and Zheyang Wu. "TFisher Tests: Optimal and Adaptive Thresholding for Combining p-Values", submitted.
See Also
stat.tfisher 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.tfisher(alpha, 100, 0.05, 0.25, eps = 0.1, mu = 1.2)