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The use of auxiliary data in robust univariate mean estimation

 

作者: Jeffrey W. Smith,  

 

期刊: Communications in Statistics - Simulation and Computation  （Taylor Available online 1990）
卷期: Volume 19, issue 3  

页码: 787-807

 

ISSN:0361-0918

 

年代: 1990

 

DOI:10.1080/03610919008812888

 

出版商: Marcel Dekker, Inc.

 

关键词: robust regression;outlier identification. Consider the problem of estimating the mean of a variable;the observations of which are suspected to be contaminated by gross errors. Robust/resistant statistical estimators that downweight the influence of outlyi

 

数据来源: Taylor

 

摘要:

Consider the problem of estimating the mean of a distribution in which the observed data are believed to be highly susceptible to gross errors (i.e., a false reading of the true value of the variate). In such situations, so-called robust statistical techniques have been found to be useful. In a nutshell, the essence of robust location estimation is the downweighting of the influence of outliers, where the outlying status of an observation is determined either by its relative order in the sample or according to its distance from the estimate of location.

 

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