fdr.adjust: Function to calculate FDR adjusted p-values

In hdi: High-Dimensional Inference

Description

Calculates FDR adjusted p-values similar to R-function p.adjust but *without* adjustment for multiplicity.

Usage

fdr.adjust(p)

Arguments

p	Vector of p-values.

Details

It is assumed that the p-values are already corrected for multiplicity. P-values with a value of 1 are currently ignored.

Value

Vector of p-values.

Author(s)

Lukas Meier

References

Meinshausen, N., Meier, L. and Bühlmann, P. (2009), P-values for high-dimensional regression, Journal of the American Statistical Association 104, 1671-1681.

See Also

p.adjust

Examples

x <- matrix(rnorm(100 * 1000), nrow = 100, ncol = 1000)
y <- x[,1] * 2 + x[,2] * 2.5 + rnorm(100)

## Multi-splitting with lasso.firstq as model selector function
fit.multi <- multi.split(x, y, model.selector =lasso.firstq,
                         args.model.selector = list(q = 10))
p.adjust <- fdr.adjust(fit.multi$pval.corr)

Example output

Loading required package: scalreg
Loading required package: lars
Loaded lars 1.2

hdi documentation built on May 27, 2021, 5:07 p.m.