multipathaic: Multi-Path Stepwise Selection with AIC

Implements a multi-path forward selection algorithm using the Akaike Information Criterion (AIC) for both linear (Gaussian) and logistic (binomial) regression models. Unlike traditional stepwise methods that follow a single path, this approach explores multiple competitive model paths simultaneously by retaining near-optimal models at each step. The package includes stability estimation via bootstrap resampling and identifies plausible models based on AIC tolerance and variable stability thresholds. The information criterion is described by Akaike (1974) <doi:10.1109/TAC.1974.1100705>, and bootstrap resampling by Efron (1979) <doi:10.1214/aos/1176344552>.

Version: 0.1.3
Depends: R (≥ 3.5.0)
Imports: stats, utils
Suggests: lars, knitr, rmarkdown, shiny, shinydashboard, plotly, DT, ggplot2, readxl, htmltools, kableExtra
Published: 2026-10-28
DOI: 10.32614/CRAN.package.multipathaic (may not be active yet)
Author: Michael Obuobi [aut, cre]
Maintainer: Michael Obuobi <obuobimichael25 at gmail.com>
BugReports: https://github.com/mobuobi/multipathaic/issues
License: MIT + file LICENSE
URL: https://github.com/mobuobi/multipathaic
NeedsCompilation: no
Materials: README, NEWS
CRAN checks: multipathaic results

Documentation:

Reference manual: multipathaic.html , multipathaic.pdf
Vignettes: Multi-Path AIC Selection: Diabetes Progression Analysis (source, R code)
Multi-Path AIC Selection: Methodology (source, R code)

Downloads:

Package source: multipathaic_0.1.3.tar.gz
Windows binaries: r-devel: not available, r-release: not available, r-oldrel: not available
macOS binaries: r-release (arm64): not available, r-oldrel (arm64): multipathaic_0.1.3.tgz, r-release (x86_64): multipathaic_0.1.3.tgz, r-oldrel (x86_64): multipathaic_0.1.3.tgz

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