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

In argminCS: Argmin Inference over a Discrete Candidate Set

Perform argmin hypothesis test using Gupta's method.

Description

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

Usage

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

Arguments

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.

Value

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'

Note

This method requires independence among the dimensions.

References

\insertRef

gupta.1965argminCS

\insertRef

futschik.1995argminCS

argminCS documentation built on Aug. 8, 2025, 7:51 p.m.