[R] cluster analysis in R

[Jose Iparraguirre]

Have a look at the package mclust.
Jose
________________________________________
From: r-help-bounces at r-project.org [r-help-bounces at r-project.org] On Behalf Of Ingmar Visser [i.visser at uva.nl]
Sent: 15 November 2012 21:10
To: KitKat
Cc: r-help at r-project.org
Subject: Re: [R] cluster analysis in R

Dear KitKat,

After installing R and reading some introductory material on getting
started with R you may want to check the CRAN task view on cluster analysis:
http://cran.r-project.org/web/views/Cluster.html
which has many useful references to all kinds and flavors of clustering
techniques, hierarchical or not, selecting the nr of clusters based on some
model selection statistic, et cetera.

hth, Ingmar

On Thu, Nov 15, 2012 at 7:14 PM, KitKat <katherinewright at trentu.ca> wrote:

> I have two issues.
>
> 1-I am trying to use morphology to identify gender. I have 9 variables,
> both
> continuous and categorical. I was using two-step cluster analysis in SPSS
> because two-step could deal with different types of variables. But the
> output tells me that an animal is in cluster 1 or 2, it does not give me a
> probability (ex. 0.70 cluster 2).  I also did not want to specify that I
> want two clusters, I wanted to see if analysis would naturally give me two
> clusters. These were all advantages to using SPSS but now I'm having
> trouble.
>
> Does cluster analysis in R give probabilities?
> Which type of cluster analysis in R is best to use? I did not think
> hierarchical analysis was a great choice, but maybe I'm wrong. I don't want
> to create the average variable, I want the analysis to do it on its own.
> I'm also new to R so would have to figure out the right codes to enter,
> etc.
>
> 2-I was also told to analyze each variable on its own before including it
> in
> cluster analysis. I had first included them all then teased out which ones
> were not important, but now have been asked to do the reverse. I cannot do
> cluster analysis on one variable -for example, one variable is either
> present or absent on an individual so of course cluster analysis gives me
> two clusters, one representing present and one representing absent. I was
> told to use regression, but how can regression also not give the same
> result? I feel like it would give me a line connecting a bunch of 0s to 1s.
> I don't know what to use, or if I can analyze each variable like this
> before
> putting them into cluster analysis. I ultimately want to only use the
> smallest number of variables necessary to identify gender.
>
> I have tried reading manuals etc and talking to people at my school, but
> nothing has helped. If anyone has any insight, that would be much
> appreciated
> Thank you!
>
>
>
> --
> View this message in context:
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> Sent from the R help mailing list archive at Nabble.com.
>
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