test.bj: Multiple comparison test using Berk and Jones (BJ) statitics.
In SetTest: Group Testing Procedures for Signal Detection and Goodness-of-Fit

Description Usage Arguments Value References See Also Examples

Multiple comparison test using Berk and Jones (BJ) statitics.

1	test.bj(prob, M, k0, k1, onesided = FALSE)

`prob`	- vector of input p-values.
`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.

pvalue - the p-value of the Berk-Jones test.

bjstat - the Berk-Jones statistic.

location - the order of the input p-values to obtain BJ statistic.

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

2. Jager, Leah; Wellner, Jon A. "Goodness-of-fit tests via phi-divergences". Annals of Statistics 35 (2007).

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

stat.bj for the definition of the statistic.

test.bj(runif(10), M=diag(10), k0=1, k1=10)
#When the input are statistics#
stat.test = rnorm(20)
p.test = 2*(1 - pnorm(abs(stat.test)))
test.bj(p.test, M=diag(20), k0=1, k1=10)