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GFA
View on CRAN: Click
here
Download and install GFA package within the R console
Install from CRAN:
install.packages("GFA")
Install from Github:
library("remotes")
install_github("cran/GFA") Install by package version:
library("remotes")
install_version("GFA", "1.0.5") Attach the package and use:
library("GFA")
Maintained by
Eemeli Leppäaho
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2016-10-11
Latest Update: 2023-10-21
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.
How to cite:
Eemeli Leppäaho (2016). GFA: Group Factor Analysis. R package version 1.0.5, https://cran.r-project.org/web/packages/GFA. Accessed 04 Jun. 2026.
Previous versions and publish date:
Other packages that cited GFA R package
View GFA citation profile
Other R packages that GFA depends,
imports, suggests or enhances
Complete documentation for GFA
Functions, R codes and Examples using
the GFA R package
Some associated functions: GFA-package . getDefaultOpts . gfa . informativeNoisePrior . normalizeData . reconstruction . robustComponents . sequentialGfaPrediction . undoNormalizeData . visualizeComponents .
Some associated R codes: GFA.R . informativeNoisePrior.R . normalizeData.R . reconstruction.R . robustComponents.R . sequentialGfaPrediction.R . visualizeComponents.R . Full GFA package functions and examples
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