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Status已发表Published
TitleA stochastic representation for the lp-norm symmetric distribution and its applications
Creator
Date Issued2017
Source PublicationCommunications in Statistics: Simulation and Computation
ISSN0361-0918
Volume46Issue:8Pages:6011-6018
Abstract

The family of lp-norm symmetric distributions was proposed by Yue and Ma and is a natural generalization to the family of l1-norm symmetric distributions studied by Fang et al. In this article, we propose a stochastic representation for the lp-norm symmetric distribution for any constant p > 0. The stochastic representation is expressed through independent and identically distributed uniform U(0, 1) random variables. It is illustrated that the stochastic representation can be applied to statistical simulation and uniform experimental design. © 2017 Taylor & Francis Group, LLC.

Keywordlp-norm symmetric distribution Statistical simulation Stochastic representation Uniform design
DOI10.1080/03610918.2016.1188207
Language英语English
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Cited Times [WOS]:0   [WOS Record]     [Related Records in WOS]
Document TypeJournal article
Identifierhttp://repository.uic.edu.cn/handle/39GCC9TT/3347
CollectionResearch outside affiliated institution
Affiliation
1.University of New Haven, College of Business, West Haven, United States
2.Department of Statistics and Actuarial Science, The University of Hong Kong, Pokfulam Road, Hong Kong
Recommended Citation
GB/T 7714
Liang, Jiajuan,Ng, Kaiwang,Tian, Guoliang. A stochastic representation for the lp-norm symmetric distribution and its applications[J]. Communications in Statistics: Simulation and Computation, 2017, 46(8): 6011-6018.
APA Liang, Jiajuan, Ng, Kaiwang, & Tian, Guoliang. (2017). A stochastic representation for the lp-norm symmetric distribution and its applications. Communications in Statistics: Simulation and Computation, 46(8), 6011-6018.
MLA Liang, Jiajuan,et al."A stochastic representation for the lp-norm symmetric distribution and its applications". Communications in Statistics: Simulation and Computation 46.8(2017): 6011-6018.
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