cmdscale {mva} | R Documentation |
Classical multidimensional scaling of a data matrix.
cmdscale(d, k = 2, eig = FALSE)
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. |
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.
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 k columns whose rows give the
coordinates of the points chosen to represent the dissimilarities. |
eig |
the eigenvalues computed during the scaling process. |
The S version of this function provides for computing an additional ``fiddle'' factor suggested by Torgerson. R does not provide this option.
Seber, G. A. F. (1984). Multivariate Observations. New York: Wiley.
Torgerson, W. S. (1958). Theory and Methods of Scaling. New York: Wiley.
dist
. Also
isoMDS
and sammon
in package `MASS'.
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)