pbj {SetTest} | R Documentation |
CDF of Berk-Jones statitic under the null hypothesis.
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)