a way to obtain Euclidean distance matrices
a way to obtain Euclidean distance matrices
kdisteuclid(obj, method = c("lingoes", "cailliez", "quasi"))obj |
an object of class |
method |
a method to convert a distance matrix in a Euclidean one |
returns an object of class kdist with all distances Euclidean.
Daniel Chessel
Stéphane Dray stephane.dray@univ-lyon1.fr
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.
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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