[R] numerical differentiation in R? (for optim "SANN" parscale)

[Roger D. Peng]

'optim' does not require any differentiation of the objective function 
for the "SANN" method.  For the other four methods 'optim' will do 
numerical differentiation for you if a gradient is not provided.  
Furthermore, the 'parscale' argument has nothing to do with 
differentiation.  As far as I know, it is used to scale the values of 
the parameters before choosing candidates (so that they are roughly 
comparable). 

-roger

BORGULYA Gábor wrote:

> Dear R users,
>
> I am running a maximum likelihood model with optim. I chose the 
> simulated annealing method (method="SANN").
>
> SANN is not performing bad, but I guess it would be much more effecive 
> if I could set the `parscale' parameter.
>
> The help sais:
> `parscale' A vector of scaling values for the parameters.
>           Optimization is performed on `par/parscale' and these should
>           be comparable in the sense that a unit change in any element
>           produces about a unit change in the scaled value.
>
> Since I know the approximate optimal parameters of the function to 
> optimise I could use these values to calculate `parscale'.
> If I understand the role of `parscale' well, I have to differentiate 
> my function numerically.
>
> How can I perform the numerical differentiation in R? I thought about 
> writing a small function, but I am sure it is already written. It must 
> be present at least in some of the optimisation algorithms.
> Anyway, I couln't find it neither in the help, nor in the 
> non-internal, displayable source of optim.
>
> Could anyone tell me where to find such a function?
> And if it really is what I need for `parscale'?
>
> Thank you!
>
> Gábor