R Graphical Manual

Last data update: 2014.03.03

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R Release (3.2.3)
CranContrib
BioConductor
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Results 1 - 3 of 3 found.
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NMF : Algorithms and Framework for Nonnegative Matrix Factorization (NMF)

Package: NMF
Type: Package
Title: Algorithms and Framework for Nonnegative Matrix Factorization
(NMF)
Version: 0.20.6
Date: 2015-05-25
Author: Renaud Gaujoux, Cathal Seoighe
Maintainer: Renaud Gaujoux <renaud@tx.technion.ac.il>
Description: Provides a framework to perform Non-negative Matrix
Factorization (NMF). The package implements a set of already published algorithms
and seeding methods, and provides a framework to test, develop and plug
new/custom algorithms. Most of the built-in algorithms have been optimized
in C++, and the main interface function provides an easy way of performing
parallel computations on multicore machines.
License: GPL (>= 2)
URL: http://renozao.github.io/NMF
BugReports: http://github.com/renozao/NMF/issues
SCM: github:renozao, r-forge
LazyLoad: yes
VignetteBuilder: knitr
Depends: R (>= 3.0.0), methods, utils, pkgmaker (>= 0.20), registry,
rngtools (>= 1.2.3), cluster
Imports: graphics, stats, stringr (>= 1.0.0), digest, grid, grDevices,
gridBase, colorspace, RColorBrewer, foreach, doParallel,
ggplot2, reshape2
Suggests: RcppOctave (>= 0.11), fastICA, doMPI, bigmemory (>= 4.2),
synchronicity, corpcor, xtable, devtools, knitr, bibtex, RUnit,
mail, Biobase
Collate: 'rmatrix.R' 'nmf-package.R' 'utils.R' 'versions.R'
'algorithmic.R' 'options.R' 'grid.R' 'colorcode.R' 'atracks.R'
'aheatmap.R' 'NMF-class.R' 'transforms.R' 'Bioc-layer.R'
'NMFstd-class.R' 'NMFOffset-class.R' 'registry.R' 'heatmaps.R'
'NMFns-class.R' 'nmfModel.R' 'fixed-terms.R' 'NMFfit-class.R'
'NMFSet-class.R' 'NMFStrategy-class.R' 'NMFSeed-class.R'
'NMFStrategyFunction-class.R' 'NMFStrategyIterative-class.R'
'NMFStrategyOctave-class.R' 'NMFplots.R'
'registry-algorithms.R' 'algorithms-base.R'
'algorithms-brunet.R' 'algorithms-lnmf.R' 'algorithms-lsnmf.R'
'algorithms-pe-nmf.R' 'algorithms-siNMF.R' 'algorithms-snmf.R'
'data.R' 'extractFeatures.R' 'registry-seed.R' 'parallel.R'
'nmf.R' 'rnmf.R' 'run.R' 'seed-base.R' 'seed-ica.R'
'seed-nndsvd.R' 'setNMFClass.R' 'simulation.R' 'tests.R'
Packaged: 2015-05-25 21:34:47 UTC; renaud
NeedsCompilation: yes
Repository: CRAN
Date/Publication: 2015-05-26 08:12:33

● Data Source: CranContrib
● 26 images, 130 functions, 1 datasets
● Reverse Depends: 2

doRNG : Generic Reproducible Parallel Backend for foreach Loops

Package: doRNG
Type: Package
Title: Generic Reproducible Parallel Backend for foreach Loops
Version: 1.6
Date: 2013-09-12
Author: Renaud Gaujoux
Maintainer: Renaud Gaujoux <renaud@tx.technion.ac.il>
Description: This package provides functions to perform
reproducible parallel foreach loops, using independent
random streams as generated by L'Ecuyer's combined
multiple-recursive generator [L'Ecuyer (1999)]. It
enables to easily convert standard %dopar% loops into
fully reproducible loops, independently of the number
of workers, the task scheduling strategy, or the chosen
parallel environment and associated foreach backend.
License: GPL (>= 2)
LazyLoad: yes
URL: https://renozao.github.io/doRNG
BugReports: http://github.com/renozao/doRNG/issues
SCM: github:renozao, r-forge
VignetteBuilder: knitr
Depends: R (>= 3.0.0), foreach, rngtools (>= 1.2.4)
Imports: stats, iterators, pkgmaker (>= 0.20)
Suggests: doParallel, doMPI, doRedis, rbenchmark, RUnit, devtools,
knitr, bibtex
Collate: 'doRNG-package.R' 'doRNG.R'
Packaged: 2014-03-07 07:46:15 UTC; renaud
NeedsCompilation: no
Repository: CRAN
Date/Publication: 2014-03-07 10:06:10

● Data Source: CranContrib
● Cran Task View: HighPerformanceComputing
● 0 images, 5 functions, 0 datasets
● Reverse Depends: 0

dtwclust : Time Series Clustering Along with Optimizations for the Dynamic Time Warping Distance

Package: dtwclust
Type: Package
Title: Time Series Clustering Along with Optimizations for the Dynamic
Time Warping Distance
Version: 2.1.2
Date: 2016-06-05
Depends: R (>= 3.2.0), proxy, dtw, ggplot2, rngtools
Imports: stats, utils, methods, flexclust, caTools, reshape2, foreach,
parallel, Rcpp
Suggests: TSdist, TSclust, doParallel, testthat
LinkingTo: Rcpp
Author: Alexis Sarda-Espinosa
Maintainer: Alexis Sarda <alexis.sarda@gmail.com>
Description: Time series clustering along with optimized techniques related
to the Dynamic Time Warping distance and its corresponding lower bounds.
Implementations of partitional, hierarchical, fuzzy, k-Shape and TADPole
clustering are available. Functionality can be easily extended with
custom distance measures and centroid definitions.
URL: https://github.com/asardaes/dtwclust
BugReports: https://github.com/asardaes/dtwclust/issues
License: GPL-3
LazyData: TRUE
NeedsCompilation: yes
RoxygenNote: 5.0.1
Collate: 'DBA.R' 'NCCc.R' 'SBD.R' 'TADPole.R' 'all_cent.R' 'ddist.R'
'dtw-lb.R' 'dtw2.R' 'dtwclust-classes.R' 'dtwclust-methods.R'
'dtwclust.R' 'kcca-list.R' 'lb-improved.R' 'lb-keogh.R'
'utils.R' 'pkg.R' 'reinterpolate.R' 'shape-extraction.R'
'uciCT.R' 'zscore.R'
Packaged: 2016-06-05 23:42:51 UTC; oso
Repository: CRAN
Date/Publication: 2016-06-06 06:39:43

● Data Source: CranContrib
● 0 images, 19 functions, 0 datasets
● Reverse Depends: 0