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Status已发表Published
TitleA t -distribution plot to detect non-multinormality
Creator
Date Issued1999
Source PublicationComputational Statistics and Data Analysis
ISSN0167-9473
Volume30Issue:1Pages:31-44
Abstract

A new Q-Q plot is developed to detect non-multinormality based on Student's t-statistic. Approximate acceptance regions, which are derived from the theory of quantile processes and Monte Carlo simulation, are suggested for use together with the Q-Q plot in applications. The acceptance regions associated with the Q-Q plots for real data enhance the interpretability of the plots, and can be recommended for use together with other graphical methods and analytical methods for testing multinormality. © 1999 Elsevier Science B.V.

Keyword6209 62G10 62H15 Graphical methods Q-Q plot Testing multinormality
DOI10.1016/S0167-9473(98)00085-1
Indexed BySCIE
Language英语English
WOS Research AreaComputer Science ; Mathematics
WOS SubjectComputer Science, Interdisciplinary Applications ; Statistics & Probability
WOS IDWOS:000079125700004
Citation statistics
Cited Times:12[WOS]   [WOS Record]     [Related Records in WOS]
Document TypeJournal article
Identifierhttp://repository.uic.edu.cn/handle/39GCC9TT/3363
CollectionResearch outside affiliated institution
Affiliation
1.Department of Mathematics, Hong Kong Baptist University, Hong Kong, Hong Kong
2.Institute of Applied Mathematics, Chinese Academy of Sciences, 100080, Beijing, China
3.Depts. of Psychology and Statistics, University of California, Box 951563, Los Angeles, CA 90095-1563, United States
Recommended Citation
GB/T 7714
Liang, Jiajuan,Bentler, Peter M. A t -distribution plot to detect non-multinormality[J]. Computational Statistics and Data Analysis, 1999, 30(1): 31-44.
APA Liang, Jiajuan, & Bentler, Peter M. (1999). A t -distribution plot to detect non-multinormality. Computational Statistics and Data Analysis, 30(1), 31-44.
MLA Liang, Jiajuan,et al."A t -distribution plot to detect non-multinormality". Computational Statistics and Data Analysis 30.1(1999): 31-44.
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