pco {labdsv} | R Documentation |
Principal coordinates analysis is an eigenanalysis of distance or metric dissimilarity matrices.
pco(dis, k=2)
dis |
the distance or dissimilarity matrix object of
class "dist" returned from
|
k |
the number of dimensions to return |
pco is simply a wrapper for the cmdscale
function
of Venebles and Ripley to make plotting of the function similar to
other LabDSV functions
an object of class ‘pco’ with components:
points |
the coordinates of samples on eigenvectors |
Principal Coordinates Analysis was pioneered by Gower (1966) as an alternative to PCA better suited to ecological datasets.
of the ‘cmdscale’ function: Venebles and Ripley
of the wrapper function David W. Roberts droberts@montana.edu
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/labdsv
data(bryceveg) # returns a vegetation data.frame dis.bc <- dsvdis(bryceveg,'bray/curtis') # returns an object of class \sQuote{dist} veg.pco <- pco(dis.bc,k=4) # returns first 4 dimensions