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The linear regression model: Lpnorm estimation and the choice of p

 

作者: A. H. money,   J. F. Affleck-Graves,   M. L. Hart,   G. D. I. Barr,  

 

期刊: Communications in Statistics - Simulation and Computation  （Taylor Available online 1982）
卷期: Volume 11, issue 1  

页码: 89-109

 

ISSN:0361-0918

 

年代: 1982

 

DOI:10.1080/03610918208812247

 

出版商: Marcel Dekker, Inc.

 

关键词: generalised variance;linear regression;Lp: norm estimates;monte carlo simulation

 

数据来源: Taylor

 

摘要:

The LPnorm provides alternatives to least squares for estimating the coefficients of a linear regression model. Monte Carlo studies were performed using six different values of p (including the least squares case of p =2) and were compared by means of the relative efficiencies based on the generalised variances. Values of p other than 2 showed improvement over least squares for all non-normal error distributions. A rule for determining a suitable p on the basis of the kurtosis of the error distribution is proposed.

 

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