Re: st: are there any statistics rules that I can apply to separate numbers into groups?

["Kyle K. Hood" <kyle.hood@yale.edu>]

In mapping, univariate classification schemes are used to group features 
together.  An example is Jenks' natural breaks, which simply defines k-1 
cutoffs to minimize within-group sums of square deviations from group 
means.  Unfortunately,

. findit jenks

produces nothing.  However, there is information on the web regarding 
how to compute these cutoffs (just google it).  I'm not sure how closely 
this method relates to cluster analysis and finite mixture models.

Kyle

Partha Deb wrote:
> Although one can never be sure what's in someone else's mind, I 
> suspect you are looking for cluster analysis. -help cluster- .  Finite 
> mixture models may also be of interest. -findit fmm- .  See 
> http://users.ox.ac.uk/~polf0050/ISS%20Lecture%208.pdf for a set of 
> slides by Stephen Fisher that has an introduction to Cluster analysis 
> and finite mixture models.
>
> Best.
>
> Partha
>
>
> Ada Ma wrote:
> > Hi Statalisters,
> >
> > I am looking for a solution to a problem but I have no idea where to 
> > start.
> >
> > Let's say I have 50 packets of crisps of various weights and I would
> > like to separate these 50 packets of crisps into five groups based on
> > their weights in grams, as follows:
> >
> > 108.9702
> > 111.1337
> > 112.5217
> > 112.6697
> > 112.9962
> > 114.0323
> > 114.6699
> > 116.8646
> > 119.0719
> > 124.5645
> > 124.691
> > 126.4943
> > 126.5528
> > 133.5675
> > 134.9519
> > 140.7979
> > 144.228
> > 102.8566
> > 103.9373
> > 104.7436
> > 107.5397
> > 109.4443
> > 109.7089
> > 110.395
> > 112.1248
> > 113.6032
> > 115.6405
> > 117.1919
> > 120.0395
> > 121.0714
> > 121.7119
> > 110.1116
> > 112.0128
> > 117.6563
> > 118.2418
> > 126.0027
> > 127.8855
> > 92.21352
> > 92.45715
> > 92.953
> > 93.01508
> > 94.05335
> > 94.27259
> > 94.38242
> > 94.72507
> > 94.83315
> > 95.25914
> > 95.37813
> > 95.52933
> >
> > I don't want to separate them into five equally sized groups.  I want
> > to separate the packets into groups so that the group members are most
> > similar to one another.  I am looking for a method (or methods?) to
> > achieve this end but I don't know where to start.  If you can think of
> > any suggestion please fire away and I'd be most grateful!
> >
> > Regards,
> > Ada
> >
> >
> >   

--
Kyle Hood
Department of Economics
Yale University
New Haven, CT
website: http://www.econ.yale.edu/~kkh25

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