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The ade4 Package - NexTag Supports Open Source Initiatives

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kdist 125<br />

Details<br />

<strong>The</strong> attributs of a ’kdist’ object are:<br />

names: the names of the distances<br />

size: the number of points between distances are known<br />

labels: the labels of points<br />

euclid: a logical vector indicating whether each distance of the list is Euclidean or not.<br />

call: a call order<br />

class: object ’kdist’<br />

Value<br />

returns an object of class ’kdist’ containing a list of semidefinite matrices.<br />

Author(s)<br />

Daniel Chessel<br />

Anne B Dufour 〈dufour@biomserv.univ-lyon1.fr〉<br />

References<br />

Gower, J. C. (1966) Some distance properties of latent root and vector methods used in multivariate<br />

analysis. Biometrika, 53, 325–338.<br />

Examples<br />

# starting from a list of matrices<br />

data(yanomama)<br />

lapply(yanomama,class)<br />

kd1 = kdist(yanomama)<br />

print(kd1)<br />

# giving the correlations of Mantel's test<br />

cor(as.data.frame(kd1))<br />

pairs(as.data.frame(kd1))<br />

# starting from a list of objects 'dist'<br />

data(friday87)<br />

fri.w

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