dudi.pco {ade4}R Documentation

Principal Coordinates Analysis

Description

dudi.pco performs a principal coordinates analysis of a Euclidean distance matrix and returns the results as objects of class pco and dudi.

Usage

dudi.pco(d, row.w = "uniform", scannf = TRUE, nf = 2, 
    full = FALSE, tol = 1e-07)
scatter.pco (x, xax = 1, yax = 2, clab.row = 1, posieig = "top", 
    sub = NULL, csub = 2, ...) 

Arguments

d an object of class dist containing a Euclidean distance matrix.
row.w an optional distance matrix row weights. If not NULL, must be a vector of positive numbers with length equal to the size of the distance matrix
scannf a logical value indicating whether the eigenvalues bar plot should be displayed
nf if scannf FALSE, an integer indicating the number of kept axes
full a logical value indicating whether all the axes should be kept
tol a tolerance threshold to test whether the distance matrix is Euclidean : an eigenvalue is considered positive if it is larger than -tol*lambda1 where lambda1 is the largest eigenvalue.
x an object of class pco
xax the column number for the x-axis
yax the column number for the y-axis
clab.row a character size for the row labels
posieig if "top" the eigenvalues bar plot is upside, if "bottom" it is downside, if "none" no plot
sub a string of characters to be inserted as legend
csub a character size for the legend, used with par("cex")*csub
... further arguments passed to or from other methods

Value

dudi.pco returns a list of class pco and dudi. See dudi

Author(s)

Daniel Chessel chessel@biomserv.univ-lyon1.fr
Anne B Dufour dufour@biomserv.univ-lyon1.fr

References

Gower, J. C. (1966) Some distance properties of latent root and vector methods used in multivariate analysis. Biometrika, 53, 325–338.

Examples

data(yanomama)
gen <- quasieuclid(as.dist(yanomama$gen))
geo <- quasieuclid(as.dist(yanomama$geo))
ant <- quasieuclid(as.dist(yanomama$ant))
geo1 <- dudi.pco(geo, scann = FALSE, nf = 3)
gen1 <- dudi.pco(gen, scann = FALSE, nf = 3)
ant1 <- dudi.pco(ant, scann = FALSE, nf = 3)
plot(coinertia(ant1, gen1, scann = FALSE))

[Package ade4 version 1.4-0 Index]