Robust SE & Heteroskedasticity-consistent estimation

Hi,

I'm using maxlik with functions specified (L, his gradient & hessian).

Now I would like determine some robust standard errors of my estimators.

So I 'm try to use vcovHC, or hccm or robcov for example

but in use one of them with my result of maxlik, I've a the following
error message :

Erreur dans terms.default(object) : no terms component

Is there some attributes to give to maxlik objet for "fitting" the call
of vcovHC?
This is discussed in
   vignette("sandwich-OOP", package = "sandwich")
one of the vignettes accompanying the "sandwich" package that provides the 
vcovHC() function. At the very least, you need an estfun() method which 
extracts the gradient contributions per observation. Then you need a 
bread() function, typically based on the observed Hessian. Then you can 
compute the basic sandwich() estimators.

Best,
Z

Thank you

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Robust SE & Heteroskedasticity-consistent estimation

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