penaltyLearning: Penalty Learning

Implementations of algorithms from Learning Sparse Penalties for Change-point Detection using Max Margin Interval Regression, by Hocking, Rigaill, Vert, Bach <http://proceedings.mlr.press/v28/hocking13.html> published in proceedings of ICML2013.

Version: 2018.09.04
Depends: R (≥ 2.10), data.table (≥ 1.9.8)
Imports: geometry, ggplot2
Suggests: Segmentor3IsBack, neuroblastoma, microbenchmark, testthat, future, future.apply, directlabels (≥ 2017.03.31)
Published: 2018-09-10
Author: Toby Dylan Hocking
Maintainer: Toby Dylan Hocking <toby.hocking at r-project.org>
License: GPL-3
NeedsCompilation: yes
Materials: NEWS
CRAN checks: penaltyLearning results

Downloads:

Reference manual: penaltyLearning.pdf
Package source: penaltyLearning_2018.09.04.tar.gz
Windows binaries: r-devel: penaltyLearning_2018.09.04.zip, r-release: penaltyLearning_2018.09.04.zip, r-oldrel: penaltyLearning_2018.09.04.zip
OS X binaries: r-release: penaltyLearning_2018.09.04.tgz, r-oldrel: penaltyLearning_2018.09.04.tgz
Old sources: penaltyLearning archive

Reverse dependencies:

Reverse imports: PeakSegJoint, PeakSegOptimal
Reverse suggests: PeakSegDP

Linking:

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