Suggests: knitr, rmarkdown, testthat, RcppArmadillo, RcppProgress

Imports: Rcpp (>= 0.12.7), methods, stats, tools, whisker

Imports: Rcpp (>= 0.12.7), methods, stats

Title: Metabolite set enrichment analysis for factor loading in
Description: This package provides functions for metabolite set
enrichment analysis (MSEA) and principal component analysis
(PCA), and converting metabolite set list from your own csv
files or KEGG's tar.gz files to XML documents.  This package is
suitable for computation of MSEA for factor loading in PCA.

Title: Modeling non-uniformity in short-read rates in RNA-Seq data
Description: This package implements all the methods in the paper
"Modeling non-uniformity in short-read rates in RNA-Seq data".
Especially, it implements both the iterative glm procedure for
the Poisson linear model and the training procedure of the MART
model. The cross-validation for both of the methods is also
Packaged: Thu Dec 3 21:59:21 2009; junli07

implemented. Version 1.1 (current version) also implements the
Poisson linear model with dinucleotide composition.
Packaged: Wed Jan 27 23:25:43 2010; junli07

implemented. Version 1.1 and later also implements the Poisson
linear model with dinucleotide composition. Version 1.2
corrected a bug in expData.R. This bug leads to mis-labeled
lines in plotCoef.R, but will not change other parts like

Title: Semiparametric Bayesian Gaussian copula estimation
Maintainer: Peter D. Hoff <hoff@stat.washington.edu>
Description: This package estimates parameters of a Gaussian
copula, treating the univariate marginal distributions
as nuisance parameters as described in Hoff(2006). It also
provides a semiparametric imputation procedure for missing
Packaged: Fri Oct  6 14:07:34 2006; root

Package: msgl
Type: Package
Title: High dimensional multiclass classification using sparse group
lasso
Version: 0.1.05
Date: 2013-20-05
Author: Martin Vincent
Maintainer: Martin Vincent <vincent@math.ku.dk>
Description: Sparse group lasso multiclass classification, suitable for
high dimensional problems with many classes. Fast algorithm for
solving the multinomial sparse group lasso convex optimization
problem. This package apply template metaprogramming
techniques, therefore -- when compiling the package from source
-- a high level of optimization is needed to gain full speed
(e.g. for the GCC compiler use -O3). Use of multiple processors
for cross validation and subsampling is supported through
OpenMP. The Armadillo C++ library is used as the primary linear
algebra engine. Armadillo is licensed under the MPL 2.0. The
Armadillo C++ library is primarily developed at NICTA
(Australia) by Conrad Sanderson, with contributions from around
the world. Furthermore the package utilize various Boost
libraries, in particular the Tuple library by Jaakko Jarvi and
the Random library by Jens Maurer. The Boost libraries are
licensed under the Boost Software License.
URL: http://arxiv.org/abs/1205.1245 http://arma.sourceforge.net/,
http://www.boost.org/
License: GPL (>= 2)
LazyLoad: yes
Depends: R (>= 3.0.0), Matrix
LinkingTo: Rcpp, RcppProgress, RcppArmadillo, BH
Collate: 'msgl_multinomial.R'
Packaged: 2013-11-18 12:16:11 UTC; martin
NeedsCompilation: yes
Repository: CRAN
Date/Publication: 2013-11-18 13:51:02