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RE: st: non-linear models not converging


From   "Jacobs, David" <jacobs.184@sociology.osu.edu>
To   "'statalist@hsphsun2.harvard.edu'" <statalist@hsphsun2.harvard.edu>
Subject   RE: st: non-linear models not converging
Date   Wed, 22 May 2013 16:41:42 +0000

Another quite simple but nevertheless useful technique:  Make sure that you don't have extremely large differences in the values of your explanatory variables.   For example, I've had this problem in count models when I enter state populations in their raw form along additional explanatory variables that were much smaller such as proportions or percentages.  

If this difficulty is present, multiply your original variable by .001 or .0001 or some such and try that remedy.

Dave Jacobs

-----Original Message-----
From: owner-statalist@hsphsun2.harvard.edu [mailto:owner-statalist@hsphsun2.harvard.edu] On Behalf Of James Bernard
Sent: Wednesday, May 22, 2013 9:01 AM
To: statalist@hsphsun2.harvard.edu
Subject: Re: st: non-linear models not converging

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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