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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