| cmdscale {mva} | R Documentation |
Classical (Metric) Multidimensional Scaling
Description
Classical multidimensional scaling of a data matrix.
Usage
cmdscale(d, k = 2, eig = FALSE)
Arguments
d |
a distance structure such as that returned by |
k |
the dimension of the space which the data are to be represented in. |
eig |
indicates whether eigenvalues should be returned. |
Details
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 functions isoMDS and sammon in package
‘MASS’ provide alternative ordination techniques.
Value
If eig = FALSE, a matrix with k columns whose rows give the
coordinates of the points chosen to represent the dissimilarities.
Otherwise, a list containing the following components.
points |
a matrix with |
eig |
the eigenvalues computed during the scaling process. |
Note
The S version of this function provides for computing an additional “fiddle” factor suggested by Torgerson. R does not provide this option.
References
Seber, G. A. F. (1984). Multivariate Observations. New York: Wiley.
Torgerson, W. S. (1958). Theory and Methods of Scaling. New York: Wiley.
See Also
dist. Also
isoMDS and sammon
in package ‘MASS’.
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)