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Bootstrapping in least absolute value regression: an application to hypothesis testing

 

作者: Terry E. Dielman,   Roger C. Pfaffenberger,  

 

期刊: Communications in Statistics - Simulation and Computation  （Taylor Available online 1988）
卷期: Volume 17, issue 3  

页码: 843-856

 

ISSN:0361-0918

 

年代: 1988

 

DOI:10.1080/03610918808812699

 

出版商: Marcel Dekker, Inc.

 

关键词: L1-norm estimation;bootstrap

 

数据来源: Taylor

 

摘要:

A Monte Carlo simulation is used to study the performance of hypothesis tests for regression coefficients when least absolute value regression methods are used. In small samples, the results of the simulation suggest that using the bootstrap method to compute standard errors will provide improved test performance

 

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