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Selection of Variables in Linear Regression Using the Minimum Sum of Weighted Absolute Errors Criterion

 

作者: SubhashC. Narula,   JohnF. Wellington,  

 

期刊: Technometrics  （Taylor Available online 1979）
卷期: Volume 21, issue 3  

页码: 299-306

 

ISSN:0040-1706

 

年代: 1979

 

DOI:10.1080/00401706.1979.10489773

 

出版商: Taylor & Francis Group

 

关键词: Subset selection;Linear programming;Implicit enumeration;Relative error

 

数据来源: Taylor

 

摘要:

An efficient implicit enumeration algorithm is proposed for the problem of selecting subsets of predictor variables in a multiple linear regression model using the minimum sum of weighted absolute errors (MSWAE) criterion. The proposed algorithm is illustrated with an example. Computational experience shows that the proposed algorithm is superior to the currently available algorithm in terms of computation time and the number of iterations required to solve a problem.

 

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