Last data update: 2014.03.03

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Results 1 - 4 of 4 found.
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MAclinical : Class prediction based on microarray data and clinical parameters

Package: MAclinical
Version: 1.0-5
Date: 2010-05-11
Title: Class prediction based on microarray data and clinical
parameters
Author: Anne-Laure Boulesteix <boulesteix@ibe.med.uni-muenchen.de>.
Maintainer: Anne-Laure Boulesteix <boulesteix@ibe.med.uni-muenchen.de>
Depends: R (>= 2.4.1), party, plsgenomics, st, e1071
Suggests:
Description: 'Maclinical' implements class prediction using both
microarray data and clinical parameters. It addresses the
question of the additional predictive value of microarray data.
Class prediction is performed using a two-step method combining
(pre-validated) PLS dimension reduction and random forests.
License: GPL (>= 2)
URL: http://cran.r-project.org/web/packages/MAclinical/index.html
Packaged: 2012-10-29 08:57:15 UTC; ripley
Repository: CRAN
Date/Publication: 2012-10-29 08:57:15

● Data Source: CranContrib
● 0 images, 11 functions, 0 datasets
● Reverse Depends: 0

PSAboot : Bootstrapping for Propensity Score Analysis

Package: PSAboot
Type: Package
Title: Bootstrapping for Propensity Score Analysis
Version: 1.1.4
Date: 2016-02-25
Author: Jason Bryer <jason@bryer.org>
Maintainer: Jason Bryer <jason@bryer.org>
URL: http://jason.bryer.org/PSAboot
BugReports: https://github.com/jbryer/PSAboot/issues
Description: Bootstrapping for propensity score analysis and matching.
License: GPL
LazyLoad: yes
VignetteBuilder: knitr
Depends: R (>= 3.0), graphics, ggplot2, PSAgraphics
Imports:
utils,Matching,MatchIt,modeltools,parallel,party,psych,reshape2,rpart,TriMatch,ggthemes,stats
Suggests: devtools, knitr, multilevelPSA
RoxygenNote: 5.0.1
NeedsCompilation: no
Packaged: 2016-02-26 01:10:24 UTC; jbryer
Repository: CRAN
Date/Publication: 2016-02-26 05:49:19

● Data Source: CranContrib
● 0 images, 26 functions, 1 datasets
● Reverse Depends: 0

GetR : GetR: Calculate Guttman error trees in R

Package: GetR
Type: Package
Title: GetR: Calculate Guttman error trees in R
Version: 0.1
Date: 2013-02-16
Author: Johannes Beller, Soeren Kliem
Maintainer: Johannes Beller <johannesbeller@gmail.com>
Description: The GetR package calculates Guttman error trees, which can
be used to find homogeneous subgroups regarding Guttman errors.
Depends: party
License: GPL-3
Packaged: 2013-02-16 20:49:35 UTC; jb
NeedsCompilation: no
Repository: CRAN
Date/Publication: 2013-02-17 08:49:12

● Data Source: CranContrib
2 images, 5 functions, 0 datasets
● Reverse Depends: 0

parboost : Distributed Model-Based Boosting

Package: parboost
Title: Distributed Model-Based Boosting
Version: 0.1.4
Date: 2015-05-03
Description: Distributed gradient boosting based on the mboost package. The
parboost package is designed to scale up component-wise functional
gradient boosting in a distributed memory environment by splitting the
observations into disjoint subsets, or alternatively using bootstrap
samples (bagging). Each cluster node then fits a boosting model to its
subset of the data. These boosting models are combined in an ensemble,
either with equal weights, or by fitting a (penalized) regression
model on the predictions of the individual models on the complete
data.
Author: Ronert Obst <ronert.obst@gmail.com>
Maintainer: Ronert Obst <ronert.obst@gmail.com>
Depends: R (>= 3.0.1), parallel, mboost, party, iterators
Imports: plyr, caret, glmnet, doParallel
License: GPL-2
NeedsCompilation: no
Packaged: 2015-05-03 16:27:09 UTC; ronert
Repository: CRAN
Date/Publication: 2015-05-04 01:24:31

● Data Source: CranContrib
● 0 images, 10 functions, 1 datasets
● Reverse Depends: 0