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On the use of the Box–Cox transformation in a linear regression with a lagged dependent variable

 

作者: Kazuhiro Ohtani,  

 

期刊: Journal of Applied Statistics  (Taylor Available online 1990)
卷期: Volume 17, issue 1  

页码: 39-47

 

ISSN:0266-4763

 

年代: 1990

 

DOI:10.1080/757582645

 

出版商: Carfax Publishing Company

 

数据来源: Taylor

 

摘要:

In this paper, we show a maximum likelihood estimation procedure in the Box–Cox model when a lagged dependent variable is included among explanatory variables and the first observation of the dependent variable is random. It is shown in a numerical example that a test of a coefficientof the lagged dependent variable is sensitive to whether the first observation of the dependentvariable is random or not.

 

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