mmpca

Integrative Analysis of Several Related Data Matrices

A generalization of principal component analysis for integrative analysis. The method finds principal components that describe single matrices or that are common to several matrices. The solutions are sparse. Rank of solutions is automatically selected using cross validation. The method is described in Kallus, Johansson, Nelander and Jörnsten (2019) <arXiv:1911.04927>.

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Description file content

Package
mmpca
Title
Integrative Analysis of Several Related Data Matrices
Version
1.0.2
Author
Jonatan Kallus [aut, cre]
Maintainer
Jonatan Kallus
Description
A generalization of principal component analysis for integrative analysis. The method finds principal components that describe single matrices or that are common to several matrices. The solutions are sparse. Rank of solutions is automatically selected using cross validation. The method is described in Kallus, Johansson, Nelander and Jörnsten (2019) .
Depends
R (>= 3.3.0)
Imports
CMF (>= 1.0), digest (>= 0.6.0), gsl (>= 1.9)
LinkingTo
Rcpp, RcppEigen
License
GPL-3
LazyData
true
NeedsCompilation
yes
Encoding
UTF-8
RoxygenNote
6.0.0
Packaged
2019-12-05 09:10:26 UTC; jonatan
Repository
CRAN
Date/Publication
2019-12-05 09:50:06 UTC

install.packages('mmpca')

1.0.2

10 days ago

Jonatan Kallus

GPL-3

Depends on

R (>= 3.3.0)

Imports

CMF (>= 1.0), digest (>= 0.6.0), gsl (>= 1.9)

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