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 <>
Package repositoryView on CRAN
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plsmselect documentation built on Dec. 1, 2019, 1:11 a.m.