plsmselect: Linear and Smooth Predictor Modelling with Penalisation and Variable Selection

Fit a model with potentially many linear and smooth predictors. Interaction effects can also be quantified. Variable selection is done using penalisation. For l1-type penalties we use iterative steps alternating between using linear predictors (lasso) and smooth predictors (generalised additive model).

Package details

AuthorIndrayudh Ghosal [aut, cre], Matthias Kormaksson [aut]
MaintainerIndrayudh Ghosal <[email protected]>
LicenseGPL-2
Version0.2.0
Package repositoryView on CRAN
Installation Install the latest version of this package by entering the following in R:
install.packages("plsmselect")

Try the plsmselect package in your browser

Any scripts or data that you put into this service are public.

plsmselect documentation built on Dec. 1, 2019, 1:11 a.m.