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Re: st: Clustering help
From
Simon Falck <[email protected]>
To
"<[email protected]>" <[email protected]>
Subject
Re: st: Clustering help
Date
Tue, 19 Mar 2013 11:15:33 +0000
I think Nick´s suggesting is reasonable.
However, you could also consult theory on how clusters can be defined and how the number of clusters can be determined. In principle, there is no optimal number of clusters. According to Mardia et al (see reference below) the number of clusters k can be estimated as k=(n/2)^1/2. Thus if you have 35 schools the number of clusters is (35/2)^(1/2) = 4.
How many schools each clusters should contain can be determined using a range of (statistical) methods. For instance, you could use the Ward method which minimizes the variance within each cluster and thus maximizes the (empirical) homogeneity within each cluster of schools. This method implies you that your schools within each clusters will be relatively "similar" and that you do not interfere in the "selection procedure" and thus in choosing how many schools there "should be" in each cluster.
For more information, see e.g.
Mardia, Kenb, and Bibby (1979) Multivariate Analysis. Academic Press. London. Pages 360-384.
Romesburg (2004) Cluster Analysis for Researchers. Lulu press. North Carolina. Pages 31-34.
Simon
On 18 mar 2013, at 18:37, Nick Cox <[email protected]> wrote:
> I'd plot a map and identify clusters by eye. (Seriously.)
>
> Nick
>
> On Mon, Mar 18, 2013 at 7:15 AM, Ron Wendt <[email protected]> wrote:
>
>> I'm looking to cluster some geocoded data into a specific
>> number of clusters all of the same size. For example, I want to make
>> 7 clusters of 5 schools each.
>> The best I've found so far is: cluster kmeans lat long, k(7).
>> However, this doesn't let me specify the number of schools that should
>> be in each cluster. Is there another/better way to do this?
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