TFisher (version 0.2.0)

stat.soft.omni: Construct omnibus soft-thresholding Fisher's p-value combination statistic.

Description

Construct omnibus soft-thresholding Fisher's p-value combination statistic.

Usage

stat.soft.omni(p, TAU1, M = NULL)

Arguments

p

- input p-values.

TAU1

- a vector of truncation parameters (=normalization parameters). Must be in non-descending order.

M

- correlation matrix of the input statistics. Default = NULL assumes independence.

Value

omni - omnibus soft-thresholding statistic.

pval - p-values of each soft-thresholding tests.

Details

Let $x_i$, $i=1,...,n$ be a sequence of individual statistics with correlation matrix M, $p_i$ be the corresponding two-sided p-values, then the soft-thresholding statistics $$Sof{t}_j=\sum _{i=1}^n-2\log (p_i/{\tau }_{1j})I(p_i\le {\tau }_{1j})$$, $j=1,...,d$. The omnibus test statistic is the minimum p-value of these soft-thresholding tests, $$W_o=mi{n}_j{G}_j(Sof{t}_j)$$, where $G_j$ is the survival function of $Sof{t}_j$.

References

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

Examples

# NOT RUN {
pval = runif(20)
TAU1 = c(0.01, 0.05, 0.5, 1)
stat.soft.omni(p=pval, TAU1=TAU1)
M = matrix(0.3,20,20) + diag(1-0.3,20)
stat.soft.omni(p=pval, TAU1=TAU1, M=M)
# }