select_method is a helper function that chooses the principle for
computing the null distribution of a two-sample test.
select_method(x, y, method, test.name, n.rep)A character string, which specifies the principle for computing the null distribution.
a (non-empty) numeric vector of data values.
a (non-empty) numeric vector of data values.
a character string specifying how the p-value is computed with
possible values "asymptotic" for an asymptotic test
based on a normal approximation, "permutation" for a
permutation test, and "randomization" for a randomization
test. The permutation test uses all splits of the joint sample
into two samples of sizes m and n, while the
randomization test draws n.rep random splits with
replacement. The values m and n denote the
sample sizes.
character string specifying the two-sample test for which the helper function is used.
an integer value specifying the number of random splits used to
calculate the randomization distribution if
method = "randomization".
When the principle is specified by the user, i.e. method contains only
one element, the selected method is returned. Otherwise, if the user
does not specify the principle, it depends on the sample size: When both
samples contain more than 30 observations, an asymptotic test is performed.
If one of the samples contains less than 30 observations, the null
distribution is computed via the randomization principle. The number of
replications n.rep for the randomization test needs to be specified
outside of this function. Each test function contains the argument
n.rep where this can be done.
If n.rep is larger than the maximum number of splits and
method = "randomization", a permutation test is performed.