Is a Distance Matrix Euclidean?
Confirmation of the Euclidean nature of a distance matrix by the Gower's theorem.is.euclid is used in summary.dist.
is.euclid(distmat, plot = FALSE, print = FALSE, tol = 1e-07) ## S3 method for class 'dist' summary(object, ...)
distmat |
an object of class 'dist' |
plot |
a logical value indicating whether the eigenvalues bar plot of the matrix of the term -1/2 dij² centred by rows and columns should be diplayed |
print |
a logical value indicating whether the eigenvalues of the matrix of the term -1/2 dij² centred by rows and columns should be printed |
tol |
a tolerance threshold : an eigenvalue is considered positive if it is larger than |
object |
an object of class 'dist' |
... |
further arguments passed to or from other methods |
returns a logical value indicating if all the eigenvalues are positive or equal to zero
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.
w <- matrix(runif(10000), 100, 100) w <- dist(w) summary(w) is.euclid (w) # TRUE w <- quasieuclid(w) # no correction need in: quasieuclid(w) w <- lingoes(w) # no correction need in: lingoes(w) w <- cailliez(w) # no correction need in: cailliez(w) rm(w)
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