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A Simple Method for Robust Regression.

机译:一种简单的鲁棒回归方法。

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Estimates of the parameters of a linear model are usually obtained by the method of ordinary least-squares (OLS),which is sensitive to large values of the additive error term. By dividing the sample into non-overlapping subsamples and computing the trimmed means of OLS subsample regression coefficients,the authors obtain a simple consistent and asymptotically normal initial estimate of the coefficients which can be used on one of the various robust techniques which have been recently discussed in the literature,or which can be used to trim the sample observations which have large residuals. (Modified author abstract)

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