Investigation of Infomation Criteria in the Box-Cox Transformation Model(宮田亘朗教授記念号)

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概要

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• This paper presents some simulation results of the information criteria methods applied in the identification of the Box-Cox transformation (BCT) model. The information criteria methods we discussed here are the general information criterion (GIC) and the Akaike's information criterion (AIC). By the GIC and the AIC, we fit a kth order BCT polynomial regression model to the data generated by three types of models. Except a second order polynomial regression model, the left two models are the exponential regression model and the logistic regression model.

• 香川大学の論文
• 1996-11-01

著者

• Yao Feng

  香川大学経済学部

関連論文

• Investigation of Infomation Criteria in the Box-Cox Transformation Model(宮田亘朗教授記念号)
• Empirical Analysis of the Causal Relations in Japanese and Chinese Macroeconomic Data

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