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Package: HDPenReg
Version: 0.93.1
Date: 2016-01-26
Title: High-Dimensional Penalized Regression
Authors@R: c(person("Quentin", "Grimonprez", role = c("aut","cre"), email =
"quentin.grimonprez@inria.fr"), person("Serge", "Iovleff", role = "aut"))
Copyright: inria 2013-2015
Depends: R (>= 3.0.2), rtkore (>= 0.9.2)
Imports: methods, Matrix
Description: Algorithms for lasso and fused-lasso problems: implementation of
the lars algorithm for lasso and fusion penalization and EM-based
algorithms for (logistic) lasso and fused-lasso penalization.
License: GPL (>= 2)
LinkingTo: rtkore, Rcpp
SystemRequirements: GNU make
RoxygenNote: 5.0.1
NeedsCompilation: yes
Packaged: 2016-01-26 10:15:09 UTC; grimonprez
Author: Quentin Grimonprez [aut, cre],
Serge Iovleff [aut]
Maintainer: Quentin Grimonprez <quentin.grimonprez@inria.fr>
Repository: CRAN
Date/Publication: 2016-01-26 23:06:38
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Package: blockcluster
Type: Package
Title: Coclustering Package for Binary, Categorical, Contingency and
Continuous Data-Sets
Version: 4.0.2
Encoding: UTF-8
Date: 2015-11-26
Authors@R: c( person("Serge", "Iovleff", role = c("aut","cre"), email = "Serge.Iovleff@stkpp.org")
, person("Parmeet", "Singh Bhatia", role = "aut", email = "bhatia.parmeet@gmail.com")
, person("Vincent", "Kubicki", role = "ctb", email = "Vincent.Kubicki@inria.fr")
, person("Gerard", "Goavert", role = "ctb")
, person("Vincent", "Brault", role = "ctb")
, person("Christophe", "Biernacki", role = "ctb")
, person("Gilles", "Celeux", role = "ctb"))
Copyright: Inria
Description: Simultaneous clustering of rows and columns, usually designated by
biclustering, co-clustering or block clustering, is an important technique
in two way data analysis. It consists of estimating a mixture model which
takes into account the block clustering problem on both the individual and
variables sets. The blockcluster package provides a bridge between the C++
core library and the R statistical computing environment. This package
allows to co-cluster binary, contingency, continuous and categorical
data-sets. It also provides utility functions to visualize the results.
This package may be useful for various applications in fields of Data
mining,Information retrieval, Biology, computer vision and many more. More
information about the project and comprehensive tutorial can be found on
the link mentioned in URL.
License: GPL (>= 3)
URL: https://gforge.inria.fr/projects/cocluster/
BugReports:
https://gforge.inria.fr/forum/forum.php?forum_id=11190&group_id=3679
LazyLoad: yes
Depends: R (>= 3.0.2), rtkore (>= 1.0.0)
Imports: methods
LinkingTo: Rcpp
SystemRequirements: GNU make
Collate: 'coclusterStrategy.R' 'optionclasses.R' 'onattach.R'
'RCocluster.R' 'cocluster.R' 'coclusterBinary.R'
'coclusterCategorical.R' 'coclusterContingency.R'
'coclusterContinuous.R'
NeedsCompilation: yes
Packaged: 2015-11-27 08:53:47 UTC; iovleff
RoxygenNote: 5.0.1
Author: Serge Iovleff [aut, cre],
Parmeet Singh Bhatia [aut],
Vincent Kubicki [ctb],
Gerard Goavert [ctb],
Vincent Brault [ctb],
Christophe Biernacki [ctb],
Gilles Celeux [ctb]
Maintainer: Serge Iovleff <Serge.Iovleff@stkpp.org>
Repository: CRAN
Date/Publication: 2015-11-27 11:41:12
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providing 
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