CRAN/E | plsmselect

plsmselect

Linear and Smooth Predictor Modelling with Penalisation and Variable Selection

Installation

About

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).

Key Metrics

Version 0.2.0
R ≥ 3.5.0
Published 2019-11-24 1781 days ago
Needs compilation? no
License GPL-2
CRAN checks plsmselect results

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Maintainer

Maintainer

Indrayudh Ghosal

Authors

Indrayudh Ghosal

aut / cre

Matthias Kormaksson

aut

Material

Reference manual
Package source

Vignettes

The plsmselect package

macOS

r-release

arm64

r-oldrel

arm64

r-release

x86_64

r-oldrel

x86_64

Windows

r-devel

x86_64

r-release

x86_64

r-oldrel

x86_64

Old Sources

plsmselect archive

Depends

R ≥ 3.5.0

Imports

dplyr ≥ 0.7.8
glmnet ≥ 2.0.16
mgcv ≥ 1.8.26
survival ≥ 2.43.3

Suggests

knitr
rmarkdown
kableExtra
purrr