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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