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CCAGFA (version 1.0.8)

Bayesian Canonical Correlation Analysis and Group Factor Analysis

Description

Variational Bayesian algorithms for learning canonical correlation analysis (CCA), inter-battery factor analysis (IBFA), and group factor analysis (GFA). Inference with several random initializations can be run with the functions CCAexperiment() and GFAexperiment().

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Version

Install

install.packages('CCAGFA')

Monthly Downloads

24

Version

1.0.8

License

GPL (>= 2)

Maintainer

Seppo Virtanen

Last Published

December 17th, 2015

Functions in CCAGFA (1.0.8)

CCAGFA-package

CCAGFA: Bayesian canonical correlation analysis (BCCA), inter-battery factor analysis (BIBFA), and group factor analysis (GFA)
gradEuv

Compute the cost function and its gradient
GFApred

Predict samples of one view given the other(s)
gradE

Compute the cost function and its gradient
GFAsample

Generate data from CCA/BIBFA/GFA model
GFAtrim

Simplify a CCA/BIBFA/GFA model
CCAcorr

Compute correlation between the views
getDefaultOpts

Get default options for BIBFA
GFA

Estimate a Bayesian IBFA/CCA/GFA model