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: 0.62.3
Depends: R (≥ 3.5.0)
Imports: rpart, randomForest, lattice, latticeExtra, methods
Suggests: leaps, quantreg, sp, diagram, oz, forecast, kernlab, Ecdat, mlbench, DAAGbio, car, mgcv, DAAG, MASS, ape, KernSmooth, knitr, prettydoc, rmarkdown, bookdown
Published: 2020-11-14
Author: John Maindonald
Maintainer: John Maindonald <john at statsresearch.co.nz>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: no
Materials: NEWS
CRAN checks: gamclass results

Downloads:

Reference manual: gamclass.pdf
Vignettes: Effectiveness of Airbags – 1998 to 2010 in the US
Aircraft Accident Patterns Over Time
Model Comparison Using Resampling Methods
Package source: gamclass_0.62.3.tar.gz
Windows binaries: r-devel: gamclass_0.62.3.zip, r-release: gamclass_0.62.3.zip, r-oldrel: gamclass_0.62.3.zip
macOS binaries: r-release (arm64): gamclass_0.62.3.tgz, r-release (x86_64): gamclass_0.62.3.tgz, r-oldrel: gamclass_0.62.3.tgz
Old sources: gamclass archive

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