Robust Estimation Using Least Trimmed Squares
نویسنده
چکیده
A robust procedure is proposed, starting from least trimmed squares as the initial estimator. The asymptotic distribution of the two-step and multi-step estimators is derived. This allows the use with a pre-specified efficiency under normality. It is argued that the good performance, together with the simplicity of the procedure, should make this the robust estimator of choice for applied work.
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تاریخ انتشار 2011