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Re: st: non-linear models not converging


From   Nick Cox <njcoxstata@gmail.com>
To   "statalist@hsphsun2.harvard.edu" <statalist@hsphsun2.harvard.edu>
Subject   Re: st: non-linear models not converging
Date   Wed, 22 May 2013 13:55:43 +0100

I presume focus on -nl-.

Convergence is more likely if

1. the model is actually right for the data in a qualitative sense
(easy to say, hard to define, obvious when it fits well)

2. you supply good initial guesses for the parameters (this is perhaps
the easiest one to tweak)

3. you are estimating a small number of parameters

4. you have a good ratio of data points to parameters

5. the data are not grotesquely behaved (e.g. outliers and high
skewness can be just as problematic as with linear models)

6. the model is not highly nonlinear (the textbooks are full of this)

7. I like lists to have about 7 items, so something else belongs here.

Maarten Buis should have a Euro for every time he's recommended
retreating to a simpler model when a complicated one doesn't converge,
and then adding complexity one step at a time. But it's good advice.

Nick
njcoxstata@gmail.com


On 22 May 2013 13:43, James Bernard <jamesstatalist@gmail.com> wrote:
> Hi all,
>
> I understand that the numeric methods used for estimation of models in
> Stata (and any other package) may result in a model that does not
> converge.
>
> Do you happen to know of any trick to help make the model converge? To
> increase the chance of converging?
>
> Thanks,
> James
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