mydata <- na.omit(matrix) # listwise deletion of missing
mydata <- scale(matrix) # standardize variables
fit <- kmeans(mydata, 8) # 8 cluster solution
# get cluster means
aggregate(mydata,by=list(fit$cluster),FUN=mean)
# append cluster assignment
mydata <- data.frame(mydata, fit$cluster)
library(cluster)
clusplot(mydata, fit$cluster, color=TRUE, shade=TRUE, labels=2, lines=0)
I get the following error
Error in princomp.default(x, scores = TRUE, cor = ncol(x) != 2) :
'princomp' can only be used with more units than variables
How can I fix it?
Thanks
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______________________________________________
R-h...@r-project.org mailing list
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PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
You could roll your own using a different ordination method, or you could
remove some variables from your data, or you could think about whether
the data you have are appropriate for what you're trying to do with them.
Sarah
On Tue, Dec 6, 2011 at 12:58 AM, elisacarli21 <elisac...@gmail.com> wrote:
> Dear all
> I'm trying to run a cluster analysis with R
> Here are the commands:
>
> mydata <- na.omit(matrix) # listwise deletion of missing
> mydata <- scale(matrix) # standardize variables
>
> fit <- kmeans(mydata, 8) # 8 cluster solution
> # get cluster means
> aggregate(mydata,by=list(fit$cluster),FUN=mean)
> # append cluster assignment
> mydata <- data.frame(mydata, fit$cluster)
>
> library(cluster)
> clusplot(mydata, fit$cluster, color=TRUE, shade=TRUE, labels=2, lines=0)
>
>
> I get the following error
> Error in princomp.default(x, scores = TRUE, cor = ncol(x) != 2) :
> 'princomp' can only be used with more units than variables
>
> How can I fix it?
>
> Thanks
>
--
Sarah Goslee
http://www.functionaldiversity.org