R: Discriminant coordinates/canonical variates

discrcoord {fpc} | R Documentation

## Discriminant coordinates/canonical variates

### Description

Computes discriminant coordinates, sometimes referred to as "canonical variates" as described in Seber (1984).

### Usage

    discrcoord(xd, clvecd, pool = "n", ...)

### Arguments

`xd` | the data matrix; a numerical object which can be coerced to a matrix.
`clvecd` | integer vector of class numbers; length must equal `nrow(xd)`.
`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

### Details

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.

### Value

List with the following components

`ev` | eigenvalues in descending order.
`units` | columns are coordinates of projection basis vectors. New points `x` can be projected onto the projection basis vectors by `x %*% units`
`proj` | projections of `xd` onto `units`.

### Author(s)

Christian Hennig c.hennig@ucl.ac.uk http://www.homepages.ucl.ac.uk/~ucakche/

### References

Seber, G. A. F. (1984). Multivariate Observations. New York: Wiley.

### See Also

`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.

### Examples

      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.

[Package fpc version 2.1-10 Index]