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GFA (version 1.0.5)

Group Factor Analysis

Description

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, and it has been presented originally by Virtanen et al. (2012), and extended in Klami et al. (2015) and Bunte et al. (2016) ; for details, see the citation info.

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Install

install.packages('GFA')

Monthly Downloads

300

Version

1.0.5

License

MIT + file LICENSE

Maintainer

Eemeli Lepp<e4>aho

Last Published

October 21st, 2023

Functions in GFA (1.0.5)

gfa

Gibbs sampling for group factor analysis
reconstruction

Full data reconstruction based on posterior samples
undoNormalizeData

A function for returning predictions into the original data space
informativeNoisePrior

Informative noise residual prior
sequentialGfaPrediction

Sequential prediction of new samples from observed data views to unobserved
normalizeData

Normalize data to be used by GFA
visualizeComponents

Visualize GFA components
robustComponents

Robust GFA components
GFA-package

Group factor analysis.
getDefaultOpts

A function for generating the default priors of GFA model