nonlinear regression and Excel solver

Hi all,

Earlier today I posted this question on s-news, so apologies to some for
the duplication.

Please put aside your snobbery about Microsoft products for a moment.

I am fitting population models to annual survey data for trout. For those
of you familiar with ecological models, I am working in the Lefkovitch
matrix framework; for those unfamiliar with that shorthand, the modeled
variable is a vector of abundances of fish in five size classes, with a
system of linear equations (represented by a matrix) governing survival,
advancement from smaller to larger stages, and reproduction.

So far, I have been using a likelihood approach in an Excel spreadsheet.
The spreadsheet includes the annual survey data, the Lefkovitch matrix,
and projections of the model, i.e., realizations to be compared to the
data. It computes the negative log-likelihood of each realization
assuming log-normally distributed noise and the sum of those likelihood
components. I use the Solver add-in to minimize the negative
log-likelihood over the parameters in the Lefkovitch matrix.

I have made a tentative stab at using nlminb() [minor success] and ms()
[no success] to fit the model in S-Plus, but my proficiency is such that
I still have greater flexibility fitting the models with Excel. Thus my
question for you all is ...

Is Excel?s Solver an adequate tool for numerical approximation in general
and nonlinear regression in particular? Or should I push on writing
S-Plus code?

Is anyone out there interested in assisting me with S-Plus code with the
potential payoff of collaboration on a publication in the ecological
literature?

Obviously, I would be equally enthused if an R user was interested in a
collaboration.

Thanks in advance,
Kristian