ARHT: Adaptable Regularized Hotelling's T^2 Test for High-Dimensional Data
Version 0.1.0

Perform the Adaptable Regularized Hotelling's T^2 test (ARHT) proposed by Li et al., (2016) . Both one-sample and two-sample mean test are available with various probabilistic alternative prior models. It contains a function to consistently estimate higher order moments of the population covariance spectral distribution using the spectral of the sample covariance matrix (Bai et al. (2010) ). In addition, it contains a function to sample from 3-variate chi-squared random vectors approximately with a given correlation matrix when the degrees of freedom are large.

Getting started

Package details

AuthorHaoran Li [aut, cre]
Date of publication2018-03-27 15:47:55 UTC
MaintainerHaoran Li <[email protected]>
LicenseGPL (>= 2)
Package repositoryView on CRAN
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ARHT documentation built on April 1, 2018, 12:05 p.m.