[Rd] Numerical optimisation and "non-feasible" regions

[Mathieu Ribatet]

Thanks Ben for your tips.
I'm not sure it'll be so easy to do (as the non-feasible regions depend 
on the model parameters), but I'm sure it's worth giving a try.
Thanks !!!
Best,

Mathieu

Ben Bolker a écrit :
> Mathieu Ribatet <mathieu.ribatet <at> epfl.ch> writes:
>
>   
>> Dear list,
>>
>> I'm currently writing a C code to compute the (composite) likelihood -
>> well this is done but not really robust. The C code is wrapped in an R
>> one which call the optimizer routine - optim or nlm. However, the
>> fitting procedure is far from being robust as the parameter space
>> depends on the parameter - I have a covariance matrix that should be a
>> valid one for example.
>>     
>
>   One reasonably straightforward hack to deal with this is
> to add a penalty that is (e.g.) a quadratic function of the
> distance from the feasible region, if that is reasonably
> straightforward to compute -- that way your function will
> get gently pushed back toward the feasible region.
>
>   Ben Bolker
>
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