cvCovEst

An efficient cross-validated approach for covariance matrix estimation, particularly useful in high-dimensional settings. This method relies upon the theory of high-dimensional loss-based covariance matrix estimator selection developed by Boileau et al. (2022) doi:10.1080/10618600.2022.2110883 to identify the optimal estimator from among a prespecified set of candidates.

Last 30 days

This package has been downloaded 315 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 9 times.

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Last 365 days

This package has been downloaded 4,445 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 51 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.