argmin.HT.gupta: Perform argmin hypothesis test using Gupta's method.

Description

Test whether a dimension is the argmin, using the method in gupta.1965argminCS.

argmin.HT.gupta(
  data,
  r,
  sample.mean = NULL,
  stds = NULL,
  critical.val = NULL,
  alpha = 0.05,
  ...
)

A list containing:

`test.stat`	The test statistic

. `critical.value`	The critical value for the hypothesis test. Being greater than it leads to a rejection.

`ans`	'Reject' or 'Accept'

data: A n by p data matrix; each of its row is a p-dimensional sample.
r: The dimension of interest for hypothesis test.
sample.mean: The sample mean of the n samples in data; defaults to NULL. It can be calculated via colMeans(data). If performing multiple tests across dimensions, pre-computing sample.mean and critical.val can significantly reduce computation time.
stds: A vector of the same (population) standard deviations for all dimensions; defaults to a vector of 1's. These are used to standardize the sample means.
critical.val: The quantile for the hypothesis test; defaults to NULL. It can be calculated via get.quantile.gupta.selection. If your experiment involves hypothesis testing over more than one dimension, pass a quantile to speed up computation.
alpha: The significance level of the hypothesis test; defaults to 0.05.
...: Additional argument to get.quantile.gupta.selection. A correct argument name needs to be specified if it is used.

gupta.1965argminCS

futschik.1995argminCS