kdisteuclid: a way to obtain Euclidean distance matrices

Description

a way to obtain Euclidean distance matrices

Usage

kdisteuclid(obj, method = c("lingoes", "cailliez", "quasi"))

Arguments

obj

an object of class kdist

method

a method to convert a distance matrix in a Euclidean one

Value

returns an object of class kdist with all distances Euclidean.

References

Gower, J.C. and Legendre, P. (1986) Metric and Euclidean properties of dissimilarity coefficients. Journal of Classification, 3, 5--48.

Cailliez, F. (1983) The analytical solution of the additive constant problem. Psychometrika, 48, 305--310.

Lingoes, J.C. (1971) Somme boundary conditions for a monotone analysis of symmetric matrices. Psychometrika, 36, 195--203.

Legendre, P. and Anderson, M.J. (1999) Distance-based redundancy analysis: testing multispecies responses in multifactorial ecological experiments. Ecological Monographs, 69, 1--24.

Legendre, P., and L. Legendre. (1998) Numerical ecology, 2nd English edition edition. Elsevier Science BV, Amsterdam.

Examples

Run this code

# NOT RUN {
w <- c(0.8, 0.8, 0.377350269, 0.8, 0.377350269, 0.377350269) # see ref.
w <- kdist(w)
w1 <- c(kdisteuclid(kdist(w), "lingoes"), kdisteuclid(kdist(w), "cailliez"), 
  kdisteuclid(kdist(w), "quasi"))
print(w, print = TRUE)
print(w1, print = TRUE)

data(eurodist)
par(mfrow = c(1, 3))
eu1 <- kdist(eurodist) # an object of class 'dist'
plot(data.frame(unclass(c(eu1, kdisteuclid(eu1, "quasi")))), asp = 1)
title(main = "Quasi")
abline(0,1)
plot(data.frame(unclass(c(eu1, kdisteuclid(eu1, "lingoes")))), asp = 1)
title(main = "Lingoes")
abline(0,1)
plot(data.frame(unclass(c(eu1, kdisteuclid(eu1, "cailliez")))), asp = 1)
title(main = "Cailliez")
abline(0,1)
# }

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