I'm using R to perform an hierarchical clustering. As a first approach I used hclust
and performed the following steps:
as.dist
function to transform it in a dist
object hclust
on the dist
object Here's the R code:
distm <- read.csv("distMatrix.csv")
d <- as.dist(distm)
hclust(d, "ward")
At this point I would like to do something similar with the function pvclust
; however, I cannot because it's not possible to pass a precomputed dist
object. How can I proceed considering that I'm using a distance not available among those provided by the dist
function of R?
I've tested the suggestion of Vincent, you can do the following (my data set is a dissimilarity matrix):
# Import you data
distm <- read.csv("distMatrix.csv")
d <- as.dist(distm)
# Compute the eigenvalues
x <- cmdscale(d,1,eig=T)
# Plot the eigenvalues and choose the correct number of dimensions (eigenvalues close to 0)
plot(x$eig,
type="h", lwd=5, las=1,
xlab="Number of dimensions",
ylab="Eigenvalues")
# Recover the coordinates that give the same distance matrix with the correct number of dimensions
x <- cmdscale(d,nb_dimensions)
# As mentioned by Stéphane, pvclust() clusters columns
pvclust(t(x))
If the dataset is not too large, you can embed your n points in a space of dimension n-1, with the same distance matrix.
# Sample distance matrix
n <- 100
k <- 1000
d <- dist( matrix( rnorm(k*n), nc=k ), method="manhattan" )
# Recover some coordinates that give the same distance matrix
x <- cmdscale(d, n-1)
stopifnot( sum(abs(dist(x) - d)) < 1e-6 )
# You can then indifferently use x or d
r1 <- hclust(d)
r2 <- hclust(dist(x)) # identical to r1
library(pvclust)
r3 <- pvclust(x)
If the dataset is large, you may have to check how pvclust
is implemented.
It's not clear to me whether you only have a distance matrix, or you computed it beforehand. In the former case, as already suggested by @Vincent, it would not be too difficult to tweak the R code of pvclust
itself (using fix()
or whatever; I provided some hints on another question on CrossValidated ). In the latter case, the authors of pvclust provide an example on how to use a custom distance function, although that means you will have to install their "unofficial version".
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