psvmSDR

A unified and user-friendly framework for applying the principal sufficient dimension reduction methods for both linear and nonlinear cases. The package has an extendable power by varying loss functions for the support vector machine, even for an user-defined arbitrary function, unless those are convex and differentiable everywhere over the support Li et al. (2011). Also, it provides a real-time sufficient dimension reduction update procedure using the principal least squares support vector machine Artemiou et al. (2021).

Last 30 days

This package has been downloaded 141 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 1 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 1,173 times in the last 365 days. Consider this 'mid-tier influencer' status—if it were a TikTok, it would get a nod from nieces and nephews. The day with the most downloads was Sep 11, 2024 with 45 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.