The Least Trimmed Squares (LTS) estimator is a popular robust regression estima-tor. It finds a sub-sample of h ‘good’ observations among n observations and applies least squares on that sub-sample. We formulate a model in which this estimator is maximum likelihood. The model has ‘outliers’ of a new type, where the outlying observations are drawn from a distribution with values outside the realized range of h ‘good’, normal ob-servations.
The LTS estimator is found to be h1/2 consistent and asymptotically standard normal in the location-scale case. Consistent estimation of h is discussed. The model differs from the commonly used -contamination models and opens the door for statisti-cal discussion on contamination schemes, new methodological developments on tests for contamination as well as inferences based on the estimated good data.
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If you would like to participate in the seminar, please send an email to the secretariat of Econometrics, eb-secr@ese.eur.nl.
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Secretariat Econometrics
Phone: +31 (0)10 408 12 59/ 12 64
Email: eb-secr@ese.eur.nl