Thank you Baptiste and Jim- I look forward to trying these ideas out
when I have a chance.
Mike
baptiste auguie wrote:
Hi,
>From what I understand of your code, you might find the following
construct useful,
funs <- c("mean", "sum", "sd", "diff")
x <- 1:10
lapply(funs, do.call, args=list(x))
and then working with lists rather than naming every object
individually. You might find mapply useful too when you have to pass
several parameters.
HTH,
baptiste
2009/11/10 bikemike42 <ml...@tamu.edu>:
Dear All,
I wrote a function for cluster analysis to compute cophenetic correlations
between dissimilarity matrices (using the VEGAN library) and cluster
analyses of every possible clustering algorithm (SEE ATTACHED)
http://old.nabble.com/file/p26288610/cor.coef.R cor.coef.R . As it is now,
it is extremely long, and for the future I was hoping to find a more
efficient way of doing this sort of thing.
To give you an outline of the function, first I create the dissimiarity
matrices using all possible methods in the VEGAN command "vegdist", then
create the clusters using all possible algorithms in "hclust" and the
dissimilarity matrices I crated, then create a table, and in one column,
list all combinations, and in the other, compute and put the cophenetic
correlation.
Any help would be appreciated! I'm pretty new to writing my own functions
but I see great time-saving potential.
Thanks!
Mike
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Michael L. Treglia
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Wildlife and Fisheries Sciences
Texas A&M University
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