GFA: Group Factor Analysis

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Factor analysis implementation for multiple data sources, i.e., for groups of variables. The whole data analysis pipeline is provided, including functions and recommendations for data normalization and model definition, as well as missing value prediction and model visualization. The model group factor analysis (GFA) is inferred with Gibbs sampling.

Author
Eemeli Leppaaho [aut, cre], Seppo Virtanen [aut], Muhammad Ammad-ud-din [ctb], Suleiman A Khan [ctb], Tommi Suvitaival [ctb], Inka Saarinen [ctb], Samuel Kaski [ctb]
Date of publication
2016-10-11 18:56:42
Maintainer
Eemeli Leppaaho <eemeli.leppaaho@aalto.fi>
License
MIT + file LICENSE
Version
1.0.0

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Man pages

getDefaultOpts
A function for generating the default priors of GFA model
gfa
Gibbs sampling for group factor analysis
GFA-package
Group factor analysis.
informativeNoisePrior
Informative noise residual prior
normalizeData
Normalize data to be used by GFA
reconstruction
Full data reconstruction based on posterior samples
robustComponents
Robust GFA components
sequentialGfaPrediction
Sequential prediction of new samples from observed data views...
undoNormalizeData
A function for returning predictions into the original data...
visualizeComponents
Visualize GFA components

Files in this package

GFA
GFA/inst
GFA/inst/CITATION
GFA/NAMESPACE
GFA/demo
GFA/demo/GFAdream.R
GFA/demo/00Index
GFA/demo/GFAexample.R
GFA/demo/GFApipeline.R
GFA/NEWS
GFA/R
GFA/R/robustComponents.R
GFA/R/normalizeData.R
GFA/R/sequentialGfaPrediction.R
GFA/R/reconstruction.R
GFA/R/GFA.R
GFA/R/informativeNoisePrior.R
GFA/R/visualizeComponents.R
GFA/MD5
GFA/DESCRIPTION
GFA/man
GFA/man/GFA-package.Rd
GFA/man/informativeNoisePrior.Rd
GFA/man/reconstruction.Rd
GFA/man/undoNormalizeData.Rd
GFA/man/robustComponents.Rd
GFA/man/getDefaultOpts.Rd
GFA/man/normalizeData.Rd
GFA/man/visualizeComponents.Rd
GFA/man/sequentialGfaPrediction.Rd
GFA/man/gfa.Rd
GFA/LICENSE