Plot maps of the factor scores of the observations for a DISTATISanalysis
Plot maps of the factor scores of the observations for a DISTATIS
analysis
Plot maps of the factor scores of the observations for a distatis
analysis. GraphDistatis gives a map of the factor scores for the observations. The labels of the observations are plotted by defaults but can be omitted (see the nude=TRUE option).
FS: The factor scores of the observations ($res4Splus$Ffrom distatis).
axis1: The dimension for the horizontal axis of the plots.
axis2: The dimension for the vertical axis of the plots.
constraints: constraints for the axes
item.colors: A I∗1 matrix (with I = # observations) of color names for the observations. If NULL (default), prettyGraphs chooses.
ZeTitle: General title for the plots.
nude: (default FALSE) When nude is TRUE the labels for the observations are not plotted (useful when editing the graphs for publication).
Ctr: Contributions of each observation. If NULL (default), these are computed from FS
Returns
constraints: A set of plot constraints that are returned.
item.colors: A set of colors for the observations are returned.
Details
Note that, in the current version, the graphs are plotted as R-plots and are not passed back by the routine. So the graphs need to be saved "by hand" from the R graphic windows. We plan to improve this in a future version.
Examples
# 1. Load the DistAlgo data set (available from the DistatisR package)data(DistAlgo)# DistAlgo is a 6*6*4 Array (face*face*Algorithm)#-----------------------------------------------------------------------------# 2. Call the DISTATIS routine with the array of distance (DistAlgo) as parameterDistatisAlgo <- distatis(DistAlgo)# 3. Plot the compromise map with the labels for the first 2 dimensions# DistatisAlgo$res4Splus$F are the factors scores for the 6 observations (i.e., faces)# DistatisAlgo$res4Splus$PartialF are the partial factors scores##(i.e., one set of factor scores per algorithm) GraphDistatisCompromise(DistatisAlgo$res4Splus$F)
References
The plots are similar to the graphs from
Abdi, H., Valentin, D., O'Toole, A.J., & Edelman, B. (2005). DISTATIS: The analysis of multiple distance matrices. Proceedings of the IEEE Computer Society: International Conference on Computer Vision and Pattern Recognition. (San Diego, CA, USA). pp. 42-47.