criticalVector: Critical vector

In angeella/ARIpermutation: Permutation-Based All-Resolutions Inference

Critical vector

Description

Compute critical vector curve.

Usage

criticalVector(pvalues, family = "simes", alpha = 0.05, lambda, delta = 1, m = NULL)

Arguments

pvalues	Matrix of pvalues with dimensions m \times B used instead of the data matrix X. Default to NULL.
family	String character. Name of the family confidence envelope to compute the critical vector from "simes", "aorc", "beta", "higher.criticism", and "power". Default to "simes".
alpha	Numeric value in '[0,1]'. \alpha level to control the family-wise error rate. Default to 0.05.
lambda	Numeric value. \lambda value computed by lambdaOpt. Default to 1.
delta	Numeric value. \delta value. Please see the reference below. Default to 1.
m	Numeric value. Number of hypothesis. Default to NULL.

Value

Numeric vector. Critical vector curve with length m.

Author(s)

Angela Andreella

References

Andreella, A., Hemerik, J., Finos, L., Weeda, W., & Goeman, J. (2023). Permutation-based true discovery proportions for functional magnetic resonance imaging cluster analysis. Statistics in Medicine, 42(14), 2311-2340.

See Also

lambdaOpt

Examples

db <- simulateData(pi0 = 0.8, m = 100, n = 20, rho = 0)
out <- pARI::signTest(X = db)
pv <- cbind(out$pv, out$pv_H0)
cv <- criticalVector(pvalues = pv, family = "simes", lambda = 1)
plot(sort(pv[,1]), type = "l")
lines(cv)

angeella/ARIpermutation documentation built on Sept. 12, 2024, 5:37 p.m.