gg.corr.plot {CJIVE} | R Documentation |

## Function for plotting Pearson correlations between predicted and true subject scores within the simulation study described in CJIVE manuscript

### Description

Graphically displays the center and spread of chordal norms for joint/individual subject score subspaces

### Usage

```
gg.corr.plot(cor.dat, cols, show.legend = FALSE, text.size)
```

### Arguments

`cor.dat` |
data frame with at least the 5 following variables: Norm - the value of the norm for a particular subspace; Type - the subspace for which the norm is given (i.e., joint/individual score/loading for dataset X1 or X2 (except for joint scores)) Method - the method by which the subspace was estimated, e.g. CJIVE, AJIVE, R.JIVE JVE_1 and JVE_2 - labels describing the proportion of joint variation explained in each dataset (and typically the number of variables in dataset X2) |

`cols` |
a vector of colors, must have length equal to the number of methods used in the simulation |

`show.legend` |
logical (TRUE/FALSE) for whether a legend should be included in the plot. Default is FALSE |

`text.size` |
numeric value for the font size |

### Value

graphical display (via ggplot2)

*CJIVE*version 0.1.0 Index]