View source: R/nulldist_twosample.R
nulldist.twosample | R Documentation |
This function generates random samples and evaluates the test statistics for the two-sample covariance matrix test 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
nulldist.twosample(
n1,
n2 = NULL,
p,
m = 1,
nnull = 100,
nrep = 100,
mean1 = NULL,
mean2 = NULL,
parallel = TRUE,
ncores = NULL
)
n1 |
sample size of the data from the first group |
n2 |
sample size of the data from the second group. If |
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 |
mean1 |
(Optional) Mean vector of the first group for the null distribution |
mean2 |
(Optional) Mean vector of the second group for the null distribution |
parallel |
Whether to parallelize or not (default is |
ncores |
Number of cores to use (If NULL and parallel is TRUE, use 75% of all cores). If |
A list with three elements corresponding to different test statistics
Box's M test statistic
Wald test statistic
## Not run:
nulldist.twosample(n = 20, p = 100, m = 5)
## End(Not run)
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