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A Fast and Efficient Algorithm for the Estimation of Parameters in Models with the Box-and-Cox Transformation

 

作者: JohnJ. Spitzer,  

 

期刊: Journal of the American Statistical Association  (Taylor Available online 1982)
卷期: Volume 77, issue 380  

页码: 760-766

 

ISSN:0162-1459

 

年代: 1982

 

DOI:10.1080/01621459.1982.10477883

 

出版商: Taylor & Francis Group

 

关键词: Box-Cox transformation;Maximum likelihood estimation;Nonlinear least squares;Power transformation

 

数据来源: Taylor

 

摘要:

A modified Newton algorithm for the estimation of parameters in models containing the Box-Cox transformation is presented. It is shown that the usual maximum likelihood estimator for theklinear parameters and thempower transformation parameters may be specified as anm-parameter nonlinear least squares estimator. Several models containing Box-Cox transformations are estimated and the speed and efficiency of the modified algorithm compared with three other gradient estimation techniques. The modified Newton algorithm obtains the same parameter estimates, but two to four times faster.

 

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