Learn R Programming

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!

Copy Link

Version

Install

install.packages('ddsPLS')

Monthly Downloads

184

Version

1.2.1

License

MIT + file LICENSE

Maintainer

Hadrien Lorenzo

Last Published

January 30th, 2024

Functions in ddsPLS (1.2.1)

bootstrapWrap

C++ wrapper for bootstrap function
ddsPLS_App

Applet to start ddsPLS
bootstrap_Rcpp

C++ implementation of the bootstrap operations
predict.ddsPLS

Function to predict from ddsPLS objects
summary.ddsPLS

Function to sum up bootstrap performance results of the ddsPLS algorithm
plot.ddsPLS

Function to plot bootstrap performance results of the ddsPLS algorithm
print.ddsPLS

Function to sum up bootstrap performance results of the ddsPLS algorithm
modelddsPLSCpp_Rcpp

C++ code to build models, internal function
ddsPLS

Data-Driven Sparse Partial Least Squares