Tools for linear, nonlinear and nonparametric regression and classification. Novel graphical methods for assessment of parametric models using nonparametric methods. One vs. All and All vs. All multiclass classification, optional class probabilities adjustment. Nonparametric regression (k-NN) for general dimension, local-linear option. Nonlinear regression with Eickert-White method for dealing with heteroscedasticity. Utilities for converting time series to rectangular form. Utilities for conversion between factors and indicator variables. Some code related to "Statistical Regression and Classification: from Linear Models to Machine Learning", N. Matloff, 2017, CRC, ISBN 9781498710916.
Version: 1.7.0 Depends: R (≥ 3.5.0), FNN, gtools Imports: R.utils, mvtnorm, sandwich, MASS, car, data.table, glmnet, rje, text2vec, polyreg Suggests: knitr, rmarkdown, OpenImageR, cdparcoord, keras, magick, partools Published: 2022-03-30 DOI: 10.32614/CRAN.package.regtools Author: Norm Matloff [aut, cre], Robin Yancey [aut], Bochao Xin [ctb], Kenneth Lee [ctb], Rongkui Han [ctb] Maintainer: Norm Matloff <matloff at cs.ucdavis.edu> BugReports: https://github.com/matloff/regtools/issues License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] URL: https://github.com/matloff/regtools NeedsCompilation: no Materials: README In views: TeachingStatistics CRAN checks: regtools results Documentation: Downloads: Reverse dependencies: Linking:Please use the canonical form https://CRAN.R-project.org/package=regtools to link to this page.
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