nulldist.onesample: One sample null distribution generator

In dnayyala/cramp: Covariance Matrix Testing using Random Projections

One sample null distribution generator

Description

This function generates random samples and evaluates the test statistics for the identity hypothesis and reports a bootstrap random sample of average p-values. The generated values can be used to calculate the critical value for rejecting/accepting the null hypothesis

Usage

nulldist.onesample(
  n,
  p,
  m = 1,
  nnull = 100,
  nrep = 100,
  mean = NULL,
  parallel = TRUE,
  ncores = NULL
)

Arguments

n	sample size of your data
p	original dimension of your data
m	projected dimension of your data (Default value is 1)
nnull	number of repetitions of averages of pvalues
nrep	number of repetitions for each average of pvalues
mean	(Optional) Mean vector for the null distribution
parallel	Whether to parallelize or not (default is TRUE)
ncores	Number of cores to use (If NULL and parallel is TRUE, use 75% of all cores). If parallel = FALSE, this argument will be ignored.

Value

A list with three elements corresponding to different test statistics

LRT

likelihood ratio test statistic

LW

Ledoit-Wolf test statistic

John

John-Nagao test statistic

Examples

## Not run: 
  nulldist.onesample(n = 20, p = 100, m = 5)

## End(Not run)

dnayyala/cramp documentation built on June 27, 2023, 1:34 p.m.