[R] problems with numerical optimisation

[Ott Toomet]

Dear list,

this is not a particular R question but perhaps someone can help.

I am running a maximum likelihood estimation (competing risk duration
model with unobserved heterogeneity) on 30 different datasets.  The
problem is that on 2 datasets the model does not converge.  I am
interested if there are any methods, based on the gradients or (an
approximation of) the hessian which helps to determine what is the
problem.  Can anybody recommend a good textbook about numerical
optimisation?

Currently I am using 100 BFGS iterations + 100 BHHH iterations and I
have programmed analytic gradients.  The fool-proof method of
excluding the variables one-by-one and simplifying the structure is
quite a slow and not particularily insightsful.

Thanks in advance

Ott