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
Documentation
Team
Haoran Li
Insights
Last 30 days
This package has been downloaded 195 times in the last 30 days. More than a random curiosity, but not quite a blockbuster. Still, it's gaining traction! The following heatmap shows the distribution of downloads per day. Yesterday, it was downloaded 9 times.
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Last 365 days
This package has been downloaded 2,371 times in the last 365 days. Now we’re talking! This work is officially 'heard of in academic circles', just like those wild research papers on synthetic bananas. The day with the most downloads was Sep 11, 2024 with 21 downloads.
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Dependencies
- Suggests1 package