Description
Data-Driven Sparse Partial Least Squares.
Description
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.
README.md
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!