pbj: CDF of Berk-Jones statitic under the null hypothesis.

In SetTest: Group Testing Procedures for Signal Detection and Goodness-of-Fit

Description

CDF of Berk-Jones statitic under the null hypothesis.

Usage

pbj(q, M, k0, k1, onesided = FALSE)

Arguments

q	- quantile, must be a scalar.
M	- correlation matrix of input statistics (of the input p-values).
k0	- search range starts from the k0th smallest p-value.
k1	- search range ends at the k1th smallest p-value.
onesided	- TRUE if the input p-values are one-sided.

Value

The left-tail probability of the null distribution of B-J statistic at the given quantile.

References

1. Hong Zhang, Jiashun Jin and Zheyang Wu. "Distributions and Statistical Power of Optimal Signal-Detection Methods In Finite Cases", submitted.

2. Donoho, David; Jin, Jiashun. "Higher criticism for detecting sparse heterogeneous mixtures". Annals of Statistics 32 (2004).

3. Berk, R.H. & Jones, D.H. Z. "Goodness-of-fit test statistics that dominate the Kolmogorov statistics". Wahrscheinlichkeitstheorie verw Gebiete (1979) 47: 47.

See Also

stat.bj for the definition of the statistic.

Examples

pval <- runif(10)
bjstat <- stat.phi(pval, s=1, k0=1, k1=10)$value
pbj(q=bjstat, M=diag(10), k0=1, k1=10)

SetTest documentation built on May 1, 2019, 9:11 p.m.