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 |