test.hc: Multiple comparison test using Higher Criticism (HC)...

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

Description

Multiple comparison test using Higher Criticism (HC) statitics.

Usage

test.hc(prob, M, k0, k1, LS = F, ZW = F, onesided = FALSE)

Arguments

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.
LS	- if LS = T, then method of Li and Siegmund (2015) will be implemented.When n and q is very large, approximation method is prefered.
ZW	- if ZW = T, then approximation method of Zhang and Wu will be implemented.
onesided	- TRUE if the input p-values are one-sided.

Value

pvalue - The p-value of the HC test.

hcstat - HC statistic.

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

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. Li, Jian; Siegmund, David. "Higher criticism: p-values and criticism". Annals of Statistics 43 (2015).

See Also

stat.hc for the definition of the statistic.

Examples

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

Example output

$pvalue
[1] 0.417477

$hcstat
[1] 1.711132

$location
[1] 1

$pvalue
[1] 0.3501881

$hcstat
[1] 1.711132

$location
[1] 1

$pvalue
[1] 0.543255

$hcstat
[1] 1.711132

$location
[1] 1

$pvalue
[1] 0.3180273

$hcstat
[1] 1.919935

$location
[1] 1

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