ARHT
Adaptable Regularized Hotelling's T^2 Test for High-Dimensional Data
Perform the Adaptable Regularized Hotelling's T^2 test (ARHT) proposed by Li et al., (2016) doi:10.48550/arXiv.1609.08725. 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) doi:10.1111/j.1467-842X.2010.00590.x). 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.
- Version0.1.0
- R version≥ 2.10
- LicenseGPL-2
- LicenseGPL-3
- Needs compilation?No
- Last release03/27/2018
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Haoran Li
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