[RsR] Can robust estimators outperform least squares in nonlinear regression for pure Gaussian noise?

[Eduardo Conceição]

Hi,

I have recently conducted a Monte Carlo simulation study for robust univariate *nonlinear* regression estimators using small sample data taken from case studies in the chemical engineering field. The paper is available from doi:10.1016/j.compchemeng.2010.04.009

A very unusual finding was that for *pure* Gaussian error some of the robust estimators could *outperform* the least squares estimator. Even though I do not known of any theoretical result which prevents this behavior to happen, I have never seen it reported either.

I would like to known whether you find this acceptable or not and what you think might be causing it.

Thanks in advance for your help.

Eduardo L.T. Concei��o
Dept. of Chemical Engineering
University of Coimbra
Portugal
e-mail: econceicao using kanguru.pt; etc using eq.uc.pt