GraphDistatisPartial {DistatisR}

Plot maps of the factor scores and partial factor scores of the observations for a DISTATIS analysis.

Description

GraphDistatisPartial plots maps of the factor scores of the observations from a distatis analysis. GraphDistatisPartial gives a map of the factors scores of the observations plus partial factor scores, as "seen" by each of the matrices.

Usage

GraphDistatisPartial(
  FS,
  PartialFS,
  axis1 = 1,
  axis2 = 2,
  constraints = NULL,
  item.colors = NULL,
  participant.colors = NULL,
  ZeTitle = "Distatis-Partial",
  Ctr = NULL,
  color.by.observations = TRUE,
  nude = FALSE,
  lines = TRUE
)

Arguments

FS

The factor scores of the observations ($res4Splus$F from the output of distatis).

PartialFS

The partial factor scores of the observations ($res4Splus$PartialF 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 I\times 1 matrix (with I = # observations) of color names for the observations. If NULL (default), prettyGraphs chooses.

participant.colors

A I\times 1 matrix (with I = # participants) of color names for the observations. If NULL (default), prettyGraphs chooses (with function prettyGraphs::).

ZeTitle

General title for the plots.

Ctr

Contributions of each observation. If NULL (default), these are computed from FS

color.by.observations

if TRUE (default), the partial factor scores are colored by item.colors. When FALSE, participant.colors are used.

nude

When nude is TRUE the labels for the observations are not plotted (useful when editing the graphs for publication).

lines

If TRUE (default) then lines are drawn between the partial factor score of an observation and the compromise factor score of the observation.

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.

participant.colors

A set of colors for the participants 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.

Paper available from https://personal.utdallas.edu/~herve/

See Also

GraphDistatisAll GraphDistatisCompromise GraphDistatisPartial GraphDistatisBoot GraphDistatisRv distatis

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)
 GraphDistatisPartial(DistatisAlgo$res4Splus$F,DistatisAlgo$res4Splus$PartialF)