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tidyfit: Regularized Linear Modeling with Tidy Data

An extension to the 'R' tidy data environment for automated machine learning. The package allows fitting and cross validation of linear regression and classification algorithms on grouped data.

Version: 0.7.2
Depends: R (≥ 3.5)
Imports: broom, crayon, dials, dplyr, furrr, generics, magrittr, MASS, methods, progressr, purrr, rlang, rsample, stats, tibble, tidyr, utils, vctrs, yardstick
Suggests: arm, bestglm, BMS, BoomSpikeSlab, CORElearn, e1071, gaselect, gets, gglasso, ggplot2, glmnet, hfr, iml, kableExtra, knitr, lme4, lmtest, lubridate, markdown, mboost, monomvn, mRMRe, MSwM, nnet, pls, quantreg, quantregForest, randomForest, sandwich, sensitivity, shrinkTVP, stringr, rmarkdown, testthat (≥ 3.0.0)
Published: 2024-10-03
DOI: 10.32614/CRAN.package.tidyfit
Author: Johann Pfitzinger [aut, cre]
Maintainer: Johann Pfitzinger <johann.pfitzinger at gmail.com>
License: GPL-3
URL: https://tidyfit.residualmetrics.com, https://github.com/jpfitzinger/tidyfit
NeedsCompilation: no
Materials: README NEWS
CRAN checks: tidyfit results [issues need fixing before 2025-01-14]

Documentation:

Reference manual: tidyfit.pdf
Vignettes: Accessing Fitted Model Objects (source, R code)
Flowchart (source, R code)
Predicting Boston House Prices (source, R code)
Bootstrapping Confidence Intervals (source, R code)
Feature Selection (source, R code)
Multinomial Classification (source, R code)
Rolling Window Time Series Regression (source, R code)
Time-varying parameters vs. rolling windows (source, R code)

Downloads:

Package source: tidyfit_0.7.2.tar.gz
Windows binaries: r-devel: tidyfit_0.7.2.zip, r-release: tidyfit_0.7.2.zip, r-oldrel: tidyfit_0.7.2.zip
macOS binaries: r-release (arm64): tidyfit_0.7.2.tgz, r-oldrel (arm64): tidyfit_0.7.2.tgz, r-release (x86_64): tidyfit_0.7.2.tgz, r-oldrel (x86_64): tidyfit_0.7.2.tgz
Old sources: tidyfit archive

Linking:

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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.