SparseBiplots

'HJ-Biplot' is a multivariate method that allow represent multivariate data on a subspace of low dimension, in such a way that most of the variability of the information is captured in a few dimensions. This package implements three new techniques and constructs in each case the 'HJ-Biplot', adapting restrictions to reduce weights and / or produce zero weights in the dimensions, based on the regularization theories. It implements three methods of regularization: Ridge, LASSO and Elastic Net.

Last 30 days

This package has been downloaded 121 times in the last 30 days. Enough downloads to make a small wave in the niche community. The curiosity is spreading! The following heatmap shows the distribution of downloads per day. Yesterday, it was downloaded 5 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 1,883 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 Aug 21, 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.