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.
|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|
|Maintainer:||John Maindonald <john at statsresearch.co.nz>|
|License:||GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]|
|CRAN checks:||gamclass results|
Effectiveness of Airbags – 1998 to 2010 in the US
Aircraft Accident Patterns Over Time
Model Comparison Using Resampling Methods
|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-oldrel (arm64): gamclass_0.62.3.tgz, r-release (x86_64): gamclass_0.62.3.tgz, r-oldrel (x86_64): gamclass_0.62.3.tgz|
|Old sources:||gamclass archive|
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