R: Mean/variance differences discriminant coordinates

mvdcoord {fpc} | R Documentation

## Mean/variance differences discriminant coordinates

### Description

Discriminant projections as defined in Young, Marco and Odell (1987). The principle is to maximize the projection of a matrix consisting of the differences between the means of all classes and the first mean and the differences between the covariance matrices of all classes and the forst covariance matrix.

### Usage

    mvdcoord(xd, clvecd, clnum=1, sphere="mcd", ...)

### 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)`.
`clnum` | integer. Number of the class to which all differences are computed.
`sphere` | a covariance matrix or one of "mve", "mcd", "classical", "none". The matrix used for sphering the data. "mcd" and "mve" are robust covariance matrices as implemented in `cov.rob`. "classical" refers to the classical covariance matrix. "none" means no sphering and use of the raw data.
`...` | no effect

### 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

Young, D. M., Marco, V. R. and Odell, P. L. (1987). Quadratic discrimination: some results on optimal low-dimensional representation, Journal of Statistical Planning and Inference, 17, 307-319.

### See Also

`plotcluster` for straight forward discriminant plots. `discrproj` for alternatives. `rFace` for generation of the example data used below.

### Examples

      set.seed(4634)
      face <- rFace(300,dMoNo=2,dNoEy=0,p=3)
      grface <- as.integer(attr(face,"grouping"))
      mcf <- mvdcoord(face,grface)
      plot(mcf$proj,col=grface)
      # ...done in one step by function plotcluster.

[Package fpc version 2.1-10 Index]