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