ElemStatLearn: Data Sets, Functions and Examples from the Book: "The Elements of Statistical Learning, Data Mining, Inference, and Prediction" by Trevor Hastie, Robert Tibshirani and Jerome Friedman

Useful when reading the book above mentioned, in the documentation referred to as ‘the book’.

Version: 2015.6.26.2
Depends: R (≥ 2.10.0), stats
Suggests: gam, splines, MASS, class, leaps, mda, lasso2, lars, boot, prim, earth
Published: 2019-08-12
Author: Material from the book's webpage (https://web.stanford.edu/~hastie/ElemStatLearn/>), R port and packaging by Kjetil B Halvorsen
Maintainer: ORPHANED
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
URL: http://www-stat.stanford.edu/~tibs/ElemStatLearn/
NeedsCompilation: no
Materials: NEWS
In views: MachineLearning, TeachingStatistics
CRAN checks: ElemStatLearn results


Reference manual: ElemStatLearn.pdf
Package source: ElemStatLearn_2015.6.26.2.tar.gz
Windows binaries: r-devel: ElemStatLearn_2015.6.26.2.zip, r-devel-gcc8: ElemStatLearn_2015.6.26.2.zip, r-release: ElemStatLearn_2015.6.26.2.zip, r-oldrel: ElemStatLearn_2015.6.26.2.zip
OS X binaries: r-release: ElemStatLearn_2015.6.26.2.tgz, r-oldrel: ElemStatLearn_2015.6.26.2.tgz
Old sources: ElemStatLearn archive

Reverse dependencies:

Reverse suggests: directlabels, genridge, loon, tensorBSS, WeightedROC


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