DistatisR: GraphDistatisCompromise – R documentation

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GraphDistatisCompromise

Plot maps of the factor scores of the observations for a DISTATIS analysis

Description

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).

Usage

GraphDistatisCompromise(FS, axis1 = 1, axis2 = 2, constraints = NULL, item.colors = NULL, 
	ZeTitle = "Distatis-Compromise", nude = FALSE, Ctr = NULL)

Arguments

`FS`	The factor scores of the observations (`$res4Splus$F`from `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 I1* matrix (with I = # observations) of color names for the observations. If NULL (default), `prettyGraphs` chooses.
`ZeTitle`	General title for the plots.
`nude`	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

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.

Value

`constraints`	A set of plot constraints that are returned.
`item.colors`	A set of colors for the observations are returned.

Author(s)

Derek Beaton and Herve Abdi

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.

see www.utdallas.edu/~herve

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 parameter
DistatisAlgo <- 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)

DistatisR

DiSTATIS Three Way Metric Multidimensional Scaling

v1.0.1

GPL-2

Authors

Derek Beaton [aut, com, ctb], Cherise Chin Fatt [ctb], Herve Abdi [aut, cre]

Initial release

2013-07-10