# Nonlinear models which are hard to estimate

Genetic algorithms are avoided in econometry literature as often as possible, but still sometimes they are inevitable. The question is: Which well known models are the most difficult to estimate using conventional algorithms? (By Conventional algorithms I mean Gauss-Newton method, Levenberg–Marquardt algorithm, and so on)

Motivation: I want to test some heuristic methods, and I need some benchmark to be sure that this particular model is really hard to estimate.

• I'd say any model that involves lots of sines/cosines or decaying exponentials would make for badly-behaved problems. – J. M. is not a statistician Dec 17 '10 at 5:27