ade4 (version 1.01)

pcoscaled: Simplified Analysis in Principal Coordinates

Description

performs a simplified analysis in principal coordinates, using an object of class dist.

Usage

pcoscaled(distmat, tol = 1e-07)

Arguments

distmat

an object of class dist

tol

a tolerance threshold, an eigenvalue is considered as positive if it is larger than -tol*lambda1 where lambda1 is the largest eigenvalue

Value

• returns a data frame containing the Euclidean representation of the distance matrix with a total inertia equal to 1

References

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

Examples

if (require(mva, quietly = TRUE)) {
	a <- 1 / sqrt(3) - 0.2
	w <- matrix(c(0,0.8,0.8,a,0.8,0,0.8,a,
		0.8,0.8,,0,a,a,a,a,0),4,4)
	w <- as.dist(w)
	w <- cailliez(w)
	w
	pcoscaled(w)
	dist(pcoscaled(w)) # w
	dist(pcoscaled(2 * w)) # the same
	sum(pcoscaled(w)^2) # unity
}