文章基本信息

标题：Statistical diagnosis and gross error test for semiparametric linear model
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作者：Shijun Ding ; Songlin Zhang ; Weiping Jiang 等
期刊名称：Geo-spatial Information Science
印刷版ISSN：1009-5020
电子版ISSN：1993-5153
出版年度：2009
卷号：12
期号：4
页码：296-302
DOI：10.1007/s11806-009-0114-3
出版社：Taylor and Francis Ltd
摘要：This paper systematically studies the statistical diagnosis and hypothesis testing for the semiparametric linear regression model according to the theories and methods of the statistical diagnosis and hypothesis testing for parametric regression model. Several diagnostic measures and the methods for gross error testing are derived. Especially, the global and local influence analysis of the gross error on the parameter X and the nonparameter s are discussed in detail; at the same time, the paper proves that the data point deletion model is equivalent to the mean shift model for the semiparametric regression model. Finally, with one simulative computing example, some helpful conclusions are drawn.
关键词：parametric regression; semiparametric linear model; influencing analysis; statistical diagnosis; gross error testing