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A very basic implementation of k-means. Beware that morphospaces are calculated so far for the 1st and 2nd component.
KMEANS(x, ...)# S3 method for PCA KMEANS(x, centers, nax = 1:2, pch = 20, cex = 0.5, ...)
# S3 method for PCA KMEANS(x, centers, nax = 1:2, pch = 20, cex = 0.5, ...)
PCA object
additional arguments to be passed to kmeans
numeric number of centers
numeric the range of PC components to use (1:2 by default)
to draw the points
the same thing as kmeans
Other multivariate: CLUST, LDA, MANOVA_PW, MANOVA, PCA, classification_metrics, mshapes
CLUST
LDA
MANOVA_PW
MANOVA
PCA
classification_metrics
mshapes
# NOT RUN { data(bot) bp <- PCA(efourier(bot, 10)) KMEANS(bp, 2) # }
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