## Classical (Metric) Multidimensional Scaling

## Usage

    cmdscale(d, k=2, eig=FALSE)

## Arguments

`d` | a distance structure such as that returned by `dist` or a full symmetric matrix containing the dissimilarities.
`k` | the dimension of the space which the data are to be represented in.
`eig` | indicates whether eigenvalues should be returned.

## Description

Multidimensional scaling takes a set of dissimilarities and returns a set of points such that the distances between the points are approximately equal to the dissimilarities.

The funtions `isomds` and `sammon` provide alternative ordination techniques.

## Value

A list containing the following components.

`points` | a matrix with `k` columns whose rows give the coordinates of the points chosen to represent the dissimilarities.
`eig` | if requested,pthe eigenvalues computed during the scaling process.

## Note

The S version of this function provides for computing an additional ``fiddle'' factor suggested by Togerson. R does not provide this option.

## References

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

Torgerson, W. S. (1958). Theory and Methods of Scaling. New York: Wiley.

## See Also

`dist`, `isomds`, `sammon`.

## Examples

    data(eurodist)
    loc <- cmdscale(eurodist)
    x <- loc[,1]
    y <- -loc[,2]
    plot(x, y, type="n",
    	xlab="", ylab="")
    text(x, y, names(eurodist), cex=0.5)

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