Data-Driven Sparse Partial Least Squares

A sparse Partial Least Squares implementation which uses soft-threshold estimation of the covariance matrices and therein introduces sparsity. Number of components and regularization coefficients are automatically set.

Data Driven Sparse PLS(ddsPLS)

ddsPLS is a sparse PLS formulation based on soft-thresholding estimations of covariance matrices.

Installation

There is currently one way to install ddsPLS

• From the under development repository from GitHub thanks to devtools

# install.packages("devtools")
devtools::install_github("hlorenzo/ddsPLS", build_vignettes = TRUE)

Once that package is installed, you can access the vignette using that command.

vignette("ddsPLS")

It is also possible to start a built in applet using

ddsPLS_App()

and it should start an interactive interface which should look like

Thanks for using!