2008•Unpublished venueRequires access

The Choice of the Initial Estimate for Computing MM-Estimates

Marcela Svarc, Vı́ctor J. Yohai

Abstract

We show, using a Monte Carlo study, that MM-estimates with projection estimates as starting point of an iterative weighted least squares algorithm, behave more robustly than MM-estimates starting at an S-estimate and similar Gaussian efficiency. Moreover the former have a robustness behavior close to the P-estimates with an additional advantage: they are asymptotically normal making statistical inference possible.

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Key concepts: Monte Carlo method, Robustness (evolution), Inference, Gaussian, Statistical inference, Mathematics, Least-squares function approximation, Algorithm