R: Canonical Joint and Individual Variation Explained (CJIVE)

# Canonical Joint and Individual Variation Explained (CJIVE)

## Documentation for package ‘CJIVE’ version 0.1.0

- DESCRIPTION file
- Package README

## Help Pages

AdjSigVarExp | Adjust Signal Variation Explained
cc.jive | Canonical (Correlation) JIVE
cc.jive.pred | CJIVE joint subject score prediction
chord.norm.diff | Chordal norm between column-subspaces of two matrices
ConvSims_gg | Convert simulation study results
create.graph.long | Function for plotting networks with ggplot
GenerateToyData | Generate 'Toy' Data
GetSimResults_Dir | Retrieve simulation results
gg.corr.plot | Function for plotting Pearson correlations between predicted and true subject scores within the simulation study described in CJIVE manuscript
gg.load.norm.plot | Function for plotting chordal norms between estimated and true variable loading subspaces within the simulation study described in CJIVE manuscript
gg.norm.plot | Function for plotting chordal norms between estimated and true subspaces within the simulation study described in CJIVE manuscript
gg.rank.plot | Function for plotting selected joint ranks
gg.score.norm.plot | Function for plotting chordal norms between estimated and true subject score subspaces within the simulation study described in CJIVE manuscript
MatVar | Matrix variation (i.e. Frobenius norm)
MatVar2 | Alternative calculation - Matrix variation (i.e. Frobenius norm)
Melt.Sim.Cors | Converts correlations of predicted to true joint subject scores to a format conducive to ggplot2
perm.jntrank | Permutation Test for Joint Rank in CJIVE
scale_loadings | Scale and sign-correct variable loadings to assist interpretation
show.image.2 | Display a heatmap of a matrix (adapted from Erick Lock's show.image function in the r.jive package)
sjive | Simple JIVE
vec2net.l | Convert vector to network
vec2net.u | Convert vector to network