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关注这篇论文的作者
Huaizhen Qin
Alan T.K. Wan

非正态误差线性回归中 t 比率与 F 比率的性质

研究问题
误差不服从正态分布时,t 比率在什么条件下仍具有 Student t 分布,椭圆对称误差又如何影响 F 比率的分布?
方法与思路
作者推导 t 分布成立的必要充分条件,分析椭圆对称及对角协方差的特殊情形,再扩展至线性模型并考察 F 比率。
材料陈述的贡献
摘要称给出非正态误差下 t 统计量的有限样本精确依据,并反对非正态扰动一般不影响 F 统计量这一笼统判断。
阅读关注点
读全文应核对必要充分条件的具体对象、椭圆对称特殊情形的协方差限制,以及 t 与 F 结果所需条件是否不同。
阅读边界
仅据所给 RePEc 出版社摘要,完整条件与分布公式未说明,不能据此认为任意非正态误差都允许沿用通常的 t 或 F 检验。

原文摘要

In this paper we derive the necessary and sufficient conditions for the t-ratio to be Student's t distributed. In particular, it is demonstrated for a special case that under conditions of nonnormality characterized by elliptical symmetry, the t-ratio remains Student's t distributed provided that the random vector forming the t-ratio has a diagonal covariance structure. Our results also show that the findings of Magnus (2002, in A. Ullah, A.T.K. Wan, & A. Chaturvedi (eds.), Handbook of Applied Econometrics and Statistical Inference, 277–285) on the sensitivity of the t-ratio remain invariant in the elliptically symmetric distribution setting. Extension to the linear model is considered. Exact results giving finite sample justification for the t-statistic under nonnormal error terms are derived. Furthermore, the distribution of the F-ratio assuming elliptical errors is examined. Our results reject the argument by Zaman (1996, Statistical Foundations for Econometric Techniques) that nonnormality of disturbances has in general no effect on the F-statistic.The authors thank Anurag Banerjee, Judith Clarke, Kazuhiro Ohtani, and Guohua Zou for their helpful suggestions and advice during the course of this work. In particular, we are very grateful to Judith Clarke for bringing to our attention the unpublished work of D.H. Thomas and to Guohua Zou for his careful reading of an earlier version of this paper. Thanks also go to the co-editor Benedikt Pötscher and two anonymous referees for their valuable comments. The second author gratefully acknowledges financial support from the Hong Kong Research Grant Council.

笔记与分组