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Re: st: non-linear models not converging


From   James Bernard <jamesstatalist@gmail.com>
To   statalist@hsphsun2.harvard.edu
Subject   Re: st: non-linear models not converging
Date   Wed, 22 May 2013 20:59:15 +0800

Thanks Nick,

I am not writing the MLE. I am using -xtpoisson

How can I supply the initial value for the numeric solution?

Thanks,
James


On Wed, May 22, 2013 at 8:55 PM, Nick Cox <njcoxstata@gmail.com> wrote:
> 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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