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:	0.6.1
Depends:	R (≥ 3.5)
Imports:	broom, crayon, dials, dplyr, furrr, magrittr, MASS, methods, progressr, purrr, rlang, rsample, stats, tibble, tidyr, utils, yardstick
Suggests:	arm, bestglm, BMS, CORElearn, e1071, gets, glmnet, hfr, kableExtra, knitr, lme4, lmtest, lubridate, mboost, mRMRe, MSwM, pls, quantreg, randomForest, sandwich, shrinkTVP, tidyverse, rmarkdown
Published:	2023-01-21
Author:	Johann Pfitzinger [aut, cre]
Maintainer:	Johann Pfitzinger <johann.pfitzinger at gmail.com>
License:	GPL-3
URL:	https://tidyfit.unchartedml.com, https://github.com/jpfitzinger/tidyfit
NeedsCompilation:	no
Materials:	README NEWS
CRAN checks:	tidyfit results

Documentation:

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

Downloads:

Package source:	tidyfit_0.6.1.tar.gz
Windows binaries:	r-devel: tidyfit_0.6.1.zip, r-release: tidyfit_0.6.1.zip, r-oldrel: tidyfit_0.6.1.zip
macOS binaries:	r-release (arm64): tidyfit_0.6.1.tgz, r-oldrel (arm64): tidyfit_0.6.1.tgz, r-release (x86_64): tidyfit_0.6.1.tgz, r-oldrel (x86_64): tidyfit_0.6.1.tgz
Old sources:	tidyfit archive

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