| is.euclid {ade4} | R Documentation |
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 -tol*lambda1 where lambda1 is the largest eigenvalue. |
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 dray@biomserv.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)
> library(ade4) > ### Name: is.euclid > ### Title: Is a Distance Matrix Euclidean ? > ### Aliases: is.euclid summary.dist > ### Keywords: array > > ### ** Examples > > w <- matrix(runif(10000), 100, 100) > w <- dist(w) > summary(w) Class: dist Distance matrix by lower triangle : d21, d22, ..., d2n, d32, ... Size: 100 Labels: call: dist(x = w) method: euclidean Euclidean matrix (Gower 1966): TRUE > is.euclid (w) # TRUE [1] 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) > > > >