labdsv (version 1.2-0)

pco: Principal Coordinates Analysis

Description

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

Usage

pco(dis, k=2)

Arguments

dis

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

k

the number of dimensions to return

Value

• an object of class pco with components:
• points
  the coordinates of samples on eigenvectors

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.

http://ecology.msu.montana.edu/labdsv/R

See Also

cmdscale, pca, nmds, cca

Examples

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