g.ridge

Ridge regression due to Hoerl and Kennard (1970)[https://doi.org/10.1080/00401706.1970.10488634] and generalized ridge regression due to Yang and Emura (2017)[https://doi.org/10.1080/03610918.2016.1193195] with optimized tuning parameters. These ridge regression estimators (the HK estimator and the YE estimator) are computed by minimizing the cross-validated mean squared errors. Both the ridge and generalized ridge estimators are applicable for high-dimensional regressors (p>n), where p is the number of regressors, and n is the sample size.

Last 30 days

This package has been downloaded 230 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 6 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 3,125 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 Sep 11, 2024 with 27 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.