| 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)