bootPLS

Several implementations of non-parametric stable bootstrap-based techniques to determine the numbers of components for Partial Least Squares linear or generalized linear regression models as well as and sparse Partial Least Squares linear or generalized linear regression models. The package collects techniques that were published in a book chapter (Magnanensi et al. 2016, 'The Multiple Facets of Partial Least Squares and Related Methods', doi:10.1007/978-3-319-40643-5_18) and two articles (Magnanensi et al. 2017, 'Statistics and Computing', doi:10.1007/s11222-016-9651-4) and (Magnanensi et al. 2021, 'Frontiers in Applied Mathematics and Statistics', doi:10.3389/fams.2021.693126).

Last 30 days

This package has been downloaded 265 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 4 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 3,517 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 26, 2024 with 60 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.