---
title: "gamsel: Generalized Additive Model Selection"
author: "Trevor Hastie and Matt P. Wand"
date: '`r Sys.Date()`'
output:
  html_document:
  fig_caption: yes
  theme: cerulean
  toc: yes
  toc_depth: 2
vignette: >
  %\VignetteIndexEntry{gamsel}
  %\VignetteEngine{knitr::rmarkdown}
  \usepackage[utf8]{inputenc}
---

The R package [gamsel](https://cran.r-project.org/package=gamsel)
implements an algorithm for generalized additive model selection
developed by and described in [Chouldechova &
Hastie](https://doi.org/10.48550/arXiv.1506.03850). The algorithm
delivers a path of selected models that is parameterized by a positive
scalar parameter, denoted by $\lambda$. Higher values of $\lambda$
correspond to sparser models.

[In this vignette](https://hastie.su.domains/swData/gamsel/gamselVignette.pdf) we
work through some illustrative examples involving simulated and actual
data. We explain how to deal with issues arising in actual data such
as candidate predictors that are categorical, heavily skewed or
ostensibly are continuous but have a low number of unique observed
values.
