highDmean

Implements the high-dimensional two-sample test proposed by Zhang (2019) http://hdl.handle.net/2097/40235. It also implements the test proposed by Srivastava, Katayama, and Kano (2013) doi:10.1016/j.jmva.2012.08.014. These tests are particularly suitable to high dimensional data from two populations for which the classical multivariate Hotelling's T-square test fails due to sample sizes smaller than dimensionality. In this case, the ZWL and ZWLm tests proposed by Zhang (2019) http://hdl.handle.net/2097/40235, referred to as zwl_test() in this package, provide a reliable and powerful test.

Last 30 days

This package has been downloaded 130 times in the last 30 days. Now we're getting somewhere! Enough downloads to populate a lively group chat. The following heatmap shows the distribution of downloads per day. Yesterday, it was downloaded 8 times.

The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.

Last 365 days

This package has been downloaded 2,112 times in the last 365 days. That's enough downloads to impress a room full of undergrads. A commendable achievement indeed. The day with the most downloads was Jul 21, 2024 with 67 downloads.

The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.