1987•The Annals of StatisticsOpen access

The Trimmed Mean in the Linear Model

A. H. Welsh

Open full text 101 citations

Abstract

For the general linear model with independent errors, we propose and examine the large sample properties of an estimator of the regression parameter. In the location model, the estimator has the same properties as the trimmed mean and the robustness and efficiency properties of the trimmed mean carry over to the general model. The estimator depends on a preliminary estimate of the regression parameter and the residuals based on it. The properties of the adaptive estimator with data-determined trimming proportions are also investigated.

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What this paper is about

For the general linear model with independent errors, we propose and examine the large sample properties of an estimator of the regression parameter. In the location model, the estimator has the same properties as the trimmed mean and the robustness and efficiency properties of the trimmed mean carry over to the general model. The estimator depends on a preliminary estimate of the regression parameter and the residuals based on it. The properties of the adaptive estimator with data-determined trimming proportions are also investigated.

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Available abstract

For the general linear model with independent errors, we propose and examine the large sample properties of an estimator of the regression parameter. In the location model, the estimator has the same properties as the trimmed mean and the robustness and efficiency properties of the trimmed mean carry over to the general model. The estimator depends on a preliminary estimate of the regression parameter and the residuals based on it. The properties of the adaptive estimator with data-determined trimming proportions are also investigated.

Key concepts: Mathematics, Truncated mean, Estimator, Trimmed estimator, Trimming, Robust statistics, Statistics, Linear regression

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