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gamclass: Functions and Data for a Course on Modern Regression and Classification

Functions and data are provided that support a course that emphasizes statistical issues of inference and generalizability. The functions are designed to make it straightforward to illustrate the use of cross-validation, the training/test approach, simulation, and model-based estimates of accuracy. Methods considered are Generalized Additive Modeling, Linear and Quadratic Discriminant Analysis, Tree-based methods, and Random Forests.

Version: 0.62.5
Depends: R (≥ 3.5.0)
Imports: rpart, randomForest, lattice, latticeExtra, methods
Suggests: sp, kernlab, mlbench, car, mgcv, DAAG, MASS, knitr, prettydoc, rmarkdown, bookdown
Published: 2023-08-21
DOI: 10.32614/CRAN.package.gamclass
Author: John Maindonald
Maintainer: John Maindonald <john at statsresearch.co.nz>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: no
Materials: README NEWS
CRAN checks: gamclass results

Documentation:

Reference manual: gamclass.pdf
Vignettes: Effectiveness of Airbags – 1998 to 2010 in the US
Aircraft Accident Patterns Over Time
Model Comparison Using Resampling Methods

Downloads:

Package source: gamclass_0.62.5.tar.gz
Windows binaries: r-devel: gamclass_0.62.5.zip, r-release: gamclass_0.62.5.zip, r-oldrel: gamclass_0.62.5.zip
macOS binaries: r-release (arm64): gamclass_0.62.5.tgz, r-oldrel (arm64): gamclass_0.62.5.tgz, r-release (x86_64): gamclass_0.62.5.tgz, r-oldrel (x86_64): gamclass_0.62.5.tgz
Old sources: gamclass archive

Linking:

Please use the canonical form https://CRAN.R-project.org/package=gamclass to link to this page.

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.
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