stat.tfisher.omni {TFisher} | R Documentation |
Construct omnibus thresholding Fisher's (TFisher) p-value combination statistic.
Description
Construct omnibus thresholding Fisher's (TFisher) p-value combination statistic.
Usage
stat.tfisher.omni(p, TAU1, TAU2, M = NULL, MU = NULL, SIGMA2 = NULL,
P0 = NULL)
Arguments
p |
- input p-values from potentially correlated input sstatistics. |
TAU1 |
- a vector of truncation parameters. Must be in non-descending order. |
TAU2 |
- a vector of normalization parameters. Must be in non-descending order. |
M |
- correlation matrix of the input statistics. Default = NULL assumes independence |
MU |
- a vector of means of TFisher statistics. Default = NULL. |
SIGMA2 |
- a vector of variances of TFisher statistics. Default = NULL. |
P0 |
- a vector of point masses of TFisher statistics. Default = NULL. |
Details
Let ,
be a sequence of individual statistics with
correlation matrix M,
be the corresponding two-sided p-values, then the TFisher statistics
, .
The omnibus test statistic is the minimum p-value of these thresholding tests,
, where is the survival function of
.
Value
omni - omnibus TFisher statistic.
pval - p-values of each TFisher tests.
References
1. Hong Zhang and Zheyang Wu. "TFisher Tests: Optimal and Adaptive Thresholding for Combining p-Values", submitted.
Examples
pval = runif(20)
TAU1 = c(0.01, 0.05, 0.5, 1)
TAU2 = c(0.1, 0.2, 0.5, 1)
stat.tfisher.omni(p=pval, TAU1=TAU1, TAU2=TAU2)
M = matrix(0.3,20,20) + diag(1-0.3,20)
stat.tfisher.omni(p=pval, TAU1=TAU1, TAU2=TAU2, M=M)