CRAN/E | CJIVE

CJIVE

Canonical Joint and Individual Variation Explained (CJIVE)

Installation

About

Joint and Individual Variation Explained (JIVE) is a method for decomposing multiple datasets obtained on the same subjects into shared structure, structure unique to each dataset, and noise. The two most common implementations are R.JIVE, an iterative approach, and AJIVE, which uses principal angle analysis. JIVE estimates subspaces but interpreting these subspaces can be challenging with AJIVE or R.JIVE. We expand upon insights into AJIVE as a canonical correlation analysis (CCA) of principal component scores. This reformulation, which we call CJIVE, 1) provides an ordering of joint components by the degree of correlation between corresponding canonical variables; 2) uses a computationally efficient permutation test for the number of joint components, which provides a p-value for each component; and 3) can be used to predict subject scores for out-of-sample observations. Please cite the following article when utilizing this package: Murden, R., Zhang, Z., Guo, Y., & Risk, B. (2022) doi:10.3389/fnins.2022.969510.

Citation CJIVE citation info

Key Metrics

Version 0.1.0
Published 2023-01-20 455 days ago
Needs compilation? no
License MIT
License File
CRAN checks CJIVE results

Downloads

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Maintainer

Maintainer

Raphiel Murden

rmurden@emory.edu

Authors

Raphiel Murden

aut / cre

Benjamin Risk

aut

Material

README
Reference manual
Package source

macOS

r-release

arm64

r-oldrel

arm64

r-release

x86_64

r-oldrel

x86_64

Windows

r-develnot available

x86_64

r-releasenot available

x86_64

r-oldrelnot available

x86_64

Imports

rootSolve
ggplot2
reshape2
fields
gplots
psych

Suggests

testthat ≥ 3.0.0