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ade4 (version 1.7-19)

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)

Value

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

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

Author

Daniel Chessel

References

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

Examples

Run this code
    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

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