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.
Package details |
|
---|---|
Author | Norm Matloff [aut, cre] (<https://orcid.org/0000-0001-9179-6785>), Robin Yancey [aut], Bochao Xin [ctb], Kenneth Lee [ctb], Rongkui Han [ctb] |
Maintainer | Norm Matloff <matloff@cs.ucdavis.edu> |
License | GPL (>= 2) |
Version | 1.7.0 |
URL | https://github.com/matloff/regtools |
Package repository | View on CRAN |
Installation |
Install the latest version of this package by entering the following in R:
|
Any scripts or data that you put into this service are public.
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.