Computation of Distance Matrices on Quantitative Variables
computes on quantitative variables, some distance matrices as canonical, Joreskog and Mahalanobis.
dist.quant(df, method = NULL, diag = FALSE, upper = FALSE,
tol = 1e-07)df |
a data frame containing only quantitative variables |
method |
an integer between 1 and 3. If NULL the choice is made with a console message. See details |
diag |
a logical value indicating whether the diagonal of the distance matrix should be printed by ‘print.dist’ |
upper |
a logical value indicating whether the upper triangle of the distance matrix should be printed by ‘print.dist’ |
tol |
used in case 3 of |
All the distances are of type d = ||x-y||_A = sqrt((x-y)^t A (x-y))
A = Identity
A = 1 / diag(cov)
A = inv(cov)
an object of class dist
Daniel Chessel
Stéphane Dray stephane.dray@univ-lyon1.fr
data(ecomor)
if(adegraphicsLoaded()) {
g1 <- scatter(dudi.pco(dist.quant(ecomor$morpho, 3), scan = FALSE), plot = FALSE)
g2 <- scatter(dudi.pco(dist.quant(ecomor$morpho, 2), scan = FALSE), plot = FALSE)
g3 <- scatter(dudi.pco(dist(scalewt(ecomor$morpho)), scan = FALSE), plot = FALSE)
g4 <- scatter(dudi.pco(dist.quant(ecomor$morpho, 1), scan = FALSE), plot = FALSE)
G <- ADEgS(list(g1, g2, g3, g4), layout = c(2, 2))
} else {
par(mfrow = c(2, 2))
scatter(dudi.pco(dist.quant(ecomor$morpho, 3), scan = FALSE))
scatter(dudi.pco(dist.quant(ecomor$morpho, 2), scan = FALSE))
scatter(dudi.pco(dist(scalewt(ecomor$morpho)), scan = FALSE))
scatter(dudi.pco(dist.quant(ecomor$morpho, 1), scan = FALSE))
par(mfrow = c(1, 1))
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