labdsv (version 2.1-0)

pco: Principal Coordinates Analysis

Description

Principal coordinates analysis is an eigenanalysis of distance or metric dissimilarity matrices.

Usage

pco(dis, k=2)

Value

An object of class ‘pco’ with components:

points

the coordinates of samples on eigenvectors

Arguments

dis

the distance or dissimilarity matrix object of class "dist" returned from dist, vegdist, or dsvdis

k

the number of dimensions to return

Author

of the ‘cmdscale’ function: Venebles and Ripley

of the wrapper function David W. Roberts

Details

pco is simply a wrapper for the cmdscale function of Venebles and Ripley to make plotting of the function similar to other LabDSV functions

References

Gower, J.C. (1966) Some distance properties of latent root and vector methods used in multivariate analysis. Biometrika 53:325-328.

See Also

cmdscale, pca, nmds, cca

Examples

data(bryceveg) # returns a vegetation data.frame
dis.bc <- dsvdis(bryceveg,'bray/curtis')
                  # returns an object of class dist'
veg.pco <- pco(dis.bc,k=4) # returns first 4 dimensions
plot(veg.pco)