TMTI: Computes the TMTI test for a joint hypothesis given input...

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

Computes the TMTI test for a joint hypothesis given input p-values.

Description

A package to compute TMTI tests, perform closed testing procedures with quadratic shortcuts and to generate confidence sets for the number of false hypotheses among m tested hypotheses.

Usage

TMTI(
  pvals,
  n = Inf,
  tau = NULL,
  K = NULL,
  gamma = NULL,
  B = 1000,
  m_max = 100,
  is.sorted = FALSE,
  ...
)

Arguments

pvals	A vector of pvalues.
n	A positive number (or Inf) indicating which type of local minimum to consider. Defaults to Inf, corresponding to the global minimum.
tau	Number between 0 and 1 or NULL, describing the truncation level.
K	Integer between >1 and m describing the truncation index.
gamma	Function; function to be used as the gamma approximation. If NULL, then the gamma function will be bootstrapped assuming independence. Defaults to NULL.
B	Numeric; number of bootstrap replicates to be used when estimating the gamma function. If a gamma is supplied, this argument is ignored. Defaults to 1e3.
m_max	Integer; the highest number of test for which the analytical computation of the TMTI CDF is used. When m is above m_max it will be bootstrapped or user supplied instead.
is.sorted	Logical, indicating whether the supplied p-values are already is.sorted. Defaults to FALSE.
...	Additional parameters.

Value

A p-value from the TMTI test

Author(s)

Phillip B. Mogensen <[e-mail]>

Examples

## Simulate some p-values
## The first 10 are from false hypotheses, the next 10 are from true
pvals = c(
  rbeta(10, 1, 20), ## Mean value of .05
  runif(10)
)
TMTI(pvals)

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