kFWER_TMTI: kFWER_TMTI. Computes the largest rejection set possible with...

In TMTI: 'Too Many, Too Improbable' (TMTI) Test Procedures

kFWER_TMTI. Computes the largest rejection set possible with kFWER control.

Description

kFWER_TMTI. Computes the largest rejection set possible with kFWER control.

Usage

kFWER_TMTI(
  pvals,
  k,
  alpha = 0.05,
  B = 1000,
  gammaList = NULL,
  tau = NULL,
  K = NULL,
  verbose = FALSE
)

Arguments

pvals	A vector p-values.
k	An integer denoting the desired k at which to control the kFWER.
alpha	Significance level.
B	Number of bootstrap replications if gamma needs to be approximated. Not used if specifying a list of functions using the gammaList argument or if length(pvals) <= 100. Defaults to 1000.
gammaList	A list of pre-specified gamma functions. If NULL, gamma functions will be approximated via bootstrap, assuming independence. Defaults to NULL.
tau	Numerical (in (0,1)); threshold to use in tTMTI. If set to NULL, then either TMTI (default) or rtTMTI is used.
K	Integer; Number of smallest p-values to use in rtTMTI. If se to NULL, then either TMTI (default) or tTMTI is used.
verbose	Logical, indicating whether or not to print progress.

Value

The number of marginal hypotheses that can be rejected with kFWER control.

Examples

nfalse = 50
m = 100
pvals = c (
  sort(runif(nfalse, 0, 0.05 / m)),
  sort(runif(m - nfalse, 0.1, 1))
)
kFWER_TMTI (
  pvals = pvals,
  k = 5,
  alpha = 0.05,
  verbose = FALSE
)

TMTI documentation built on Aug. 10, 2022, 5:06 p.m.