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st: RE: Parameter restrictions in MLE


From   "Nick Cox" <[email protected]>
To   <[email protected]>
Subject   st: RE: Parameter restrictions in MLE
Date   Fri, 26 May 2006 10:22:42 +0100

I don't know about "best", particularly in general. 

But one way to do it is to parameterise in terms 
of e.g. a, b, 1 - (a + b). If you are lucky this 
will be enough. 

You could still have problems if the algorithm 
is happiest at e.g. a = 1.1, b = -0.9, c = 0.8. 

Nick 
[email protected] 

Deepankar Basu
 
> I am trying to do a maximum likelihood estimation where some of the
> parameters of the model are probabilities; hence they should add up to
> unity. 
> 
> What is the best way to put restrictions on the relevant 
> parameters and
> constrain them to add up to unity?

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