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CJIVE
View on CRAN: Click
here
Download and install CJIVE package within the R console
Install from CRAN:
install.packages("CJIVE")
Install from Github:
library("remotes")
install_github("cran/CJIVE") Install by package version:
library("remotes")
install_version("CJIVE", "0.1.0") Attach the package and use:
library("CJIVE")
Maintained by
Raphiel Murden
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2023-01-20
Latest Update: 2023-01-20
Description:
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) .
How to cite:
Raphiel Murden (2023). CJIVE: Canonical Joint and Individual Variation Explained (CJIVE). R package version 0.1.0, https://cran.r-project.org/web/packages/CJIVE. Accessed 07 Mar. 2026.
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Complete documentation for CJIVE
Functions, R codes and Examples using
the CJIVE R package
Some associated functions: AdjSigVarExp . ConvSims_gg . GenerateToyData . GetSimResults_Dir . MatVar . MatVar2 . Melt.Sim.Cors . cc.jive . cc.jive.pred . chord.norm.diff . create.graph.long . gg.corr.plot . gg.load.norm.plot . gg.norm.plot . gg.rank.plot . gg.score.norm.plot . perm.jntrank . scale_loadings . show.image.2 . sjive . vec2net.l . vec2net.u .
Some associated R codes: CJIVE_Functions.R . SimulationStudyFunctions.R . Utilities.R . Full CJIVE package functions and examples
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