ARHT 0.1.0

Adaptable Regularized Hotelling's T^2 Test for High-Dimensional Data

Released Mar 27, 2018 by Haoran Li

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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.



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Test Results

This package was last tested against Renjin 0.9.2644 on Jun 1, 2018.



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