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st: new package dirifit

From   Maarten buis <[email protected]>
To   [email protected]
Subject   st: new package dirifit
Date   Sun, 23 Apr 2006 16:53:24 +0100 (BST)

Thanks to Kit Baum, there is a new package available for 
download on SSC, -dirifit- by Maarten Buis, Nick Cox and 
Stephen Jenkins. dirifit fits by maximum likelihood a 
Dirichlet distribution to a set of variables. Usually these 
variables are proportions, e.g. proportions of the budget 
of municipalities spent on categories school, police, and 
other. These proportions can be made dependent on covariates, 
e.g. political orientation of ruling parties, and whether or 
not the municipality is urban.

-dirifit- is closely related to -betafit-, just as the 
Dirichlet distribution is closely related to the beta
distribution. Both model proportions, but -betafit- can 
handle only one dependent/explained/y variable, while 
-dirifit- can handle multiple dependent variables. Using the
example above: -betafit- could model the proportion of city
budget spent on e.g. police, while -dirifit- can model the 
proportions spent on all categories simultaneously. Another
way to think about it is that -betafit- and -dirifit- have
a lot in common just as -logit- and -mlogit- have a lot in

-dirifit- has two parameterization, just as -betafit-: one 
in terms of only scale parameters, and one in terms of 
location parameters and one scale parameter. The latter 
allows one to model the odds of one category versus the 
reference category, and should be most useful if one has
covariates, while the former conforms more to the 
conventional way a Dirichlet distribution is written and 
should be most useful when no covariates are used.


Maarten L. Buis
Department of Social Research Methodology
Vrije Universiteit Amsterdam
Boelelaan 1081
1081 HV Amsterdam
The Netherlands

visiting adress:
Buitenveldertselaan 3 (Metropolitan), room Z214

+31 20 5986715

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