This paper examines the problem of estimating the parameters describing system models
of quite general nonlinear and multi-variable form. The approach is a computational one in
which quantities that are intractable to evaluate exactly are approximated by sample
averages from randomized algorithms. The main contribution is to illustrate the viability
and utility of this approach by examining how high computational loads can be simply
managed using commodity hardware. The proposed algorithms and solution architectures
are profiled on concrete examples.