Simplified Analysis in Principal Coordinates
performs a simplified analysis in principal coordinates,
using an object of class dist.
pcoscaled(distmat, tol = 1e-07)
distmat |
an object of class |
tol |
a tolerance threshold, an eigenvalue is considered as positive if it is larger than |
returns a data frame containing the Euclidean representation of the distance matrix with a total inertia equal to 1
Daniel Chessel
Gower, J. C. (1966) Some distance properties of latent root and vector methods used in multivariate analysis. Biometrika, 53, 325–338.
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) # unityPlease choose more modern alternatives, such as Google Chrome or Mozilla Firefox.