Functions and data are provided that support a course that emphasizes statistical issues of inference and generalizability. Attention is restricted to a relatively small number of methods, often (misleadingly in my view) referred to as algorithms.
Version: | 0.56 |
Depends: | R (≥ 3.0.0) |
Imports: | car, mgcv, DAAG, MASS, rpart, randomForest, lattice, latticeExtra, ape, KernSmooth, methods |
Suggests: | leaps, quantreg, sp, diagram, oz, forecast, SMIR, kernlab, Ecdat, mlbench, DAAGbio, knitr |
Published: | 2015-08-20 |
Author: | John Maindonald |
Maintainer: | John Maindonald <john.maindonald at anu.edu.au> |
License: | GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
NeedsCompilation: | no |
Materials: | NEWS |
CRAN checks: | gamclass results |
Reference manual: | gamclass.pdf |
Vignettes: |
Key Ideas and Issues (Set 1 Figures) Model Output Can Deceive (Set 10) Ordination (Set 11) Limits of Statistical Learning (Set 2) Data-Based Generalization (Set 3) Linear Models (Set 4) Generalized Linear Models (Set 5) Generalized Additive Models (Set 6) Time Series (Set 7) Tree-based regression (Set 8) Discrimination and Classification (Set 9) |
Package source: | gamclass_0.56.tar.gz |
Windows binaries: | r-devel: gamclass_0.56.zip, r-release: gamclass_0.56.zip, r-oldrel: gamclass_0.56.zip |
OS X El Capitan binaries: | r-release: gamclass_0.56.tgz |
OS X Mavericks binaries: | r-oldrel: gamclass_0.56.tgz |
Old sources: | gamclass archive |
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