Discriminant coordinates/canonical variates
Computes discriminant coordinates, sometimes referred to as "canonical variates" as described in Seber (1984).
discrcoord(xd, clvecd, pool = "n", ...)
xd |
the data matrix; a numerical object which can be coerced to a matrix. |
clvecd |
integer vector of class numbers; length must equal
|
pool |
string. Determines how the within classes covariance is pooled. "n" means that the class covariances are weighted corresponding to the number of points in each class (default). "equal" means that all classes get equal weight. |
... |
no effect |
The matrix T (see Seber (1984), p. 270) is inverted by use of
tdecomp, which can be expected to give
reasonable results for singular within-class covariance matrices.
List with the following components
ev |
eigenvalues in descending order. |
units |
columns are coordinates of projection basis vectors.
New points |
proj |
projections of |
Seber, G. A. F. (1984). Multivariate Observations. New York: Wiley.
plotcluster for straight forward discriminant plots.
batcoord for discriminating projections for two classes,
so that also the differences in variance are shown (discrcoord is
based only on differences in mean).
rFace for generation of the example data used below.
set.seed(4634) face <- rFace(600,dMoNo=2,dNoEy=0) grface <- as.integer(attr(face,"grouping")) dcf <- discrcoord(face,grface) plot(dcf$proj,col=grface) # ...done in one step by function plotcluster.
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