How to use 'hclust' as function call in R

cluster-analysis, function-calls, hclust, r

Solution

Do read the help for functions you use. `?hclust` is pretty clear that the first argument `d` is a dissimilarity object, not a matrix:

Arguments:

       d: a dissimilarity structure as produced by ‘dist’.

Update

As the OP has now updated their question, what is need is

hclustfunc <- function(x) hclust(x, method="complete")
distfunc <- function(x) as.dist((1-cor(t(x)))/2)
d <- distfunc(mydata)
fit <- hclustfunc(d)

Original

What you want is

hclustfunc <- function(x, method = "complete", dmeth = "euclidean") {    
    hclust(dist(x, method = dmeth), method = method)
}

and then

fit <- hclustfunc(mydata)

works as expected. Note you can now pass in the dissimilarity coefficient method as `dmeth` and the clustering method.

Problem

I tried to construct the clustering method as function the following ways: ``` mydata <- mtcars # Here I construct hclust as a function hclustfunc <- function(x) hclust(as.matrix(x),method="complete") # Define distance metric distfunc <- function(x) as.dist((1-cor(t(x)))/2) # Obtain distance d <- distfunc(mydata) # Call that hclust function fit<-hclustfunc(d) # Later I'd do # plot(fit) ``` But why it gives the following error: ``` Error in if (is.na(n) || n > 65536L) stop("size cannot be NA nor exceed 65536") : missing value where TRUE/FALSE needed ``` What's the right way to do it?

Original source