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 |