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	Robust hypothesis testing for asymmetric nominal densities under a relative entropy tolerance
	Song, Enbin; Shi, Qingjiang; Zhu, Yunmin; Pan, Jianxi
刊名	SCIENCE CHINA-MATHEMATICS
	2018
卷号	Vol.61 No.10页码:1851-1880
关键词	Kullback-Leibler divergence robust hypothesis testing min-max problem least-favorable densities saddle point 62F03 62C20
ISSN号	1674-7283
URL标识	查看原文
内容类型	期刊论文
URI标识	http://www.corc.org.cn/handle/1471x/1869940
专题	四川大学
作者单位	1.Sichuan Univ, Dept Math, Chengdu 610064, Sichuan, Peoples R China 2.Sichuan Univ, Ctr Stat Sci, Chengdu 610064, Sichuan, Peoples R China 3.Zhejiang Sci Tech Univ, Sch Informat Sci & Technol, Hangzhou 310018, Zhejiang, Peoples R China
推荐引用方式 GB/T 7714	Song, Enbin,Shi, Qingjiang,Zhu, Yunmin,et al. Robust hypothesis testing for asymmetric nominal densities under a relative entropy tolerance[J]. SCIENCE CHINA-MATHEMATICS,2018,Vol.61 No.10:1851-1880.
APA	Song, Enbin,Shi, Qingjiang,Zhu, Yunmin,&Pan, Jianxi.(2018).Robust hypothesis testing for asymmetric nominal densities under a relative entropy tolerance.SCIENCE CHINA-MATHEMATICS,Vol.61 No.10,1851-1880.
MLA	Song, Enbin,et al."Robust hypothesis testing for asymmetric nominal densities under a relative entropy tolerance".SCIENCE CHINA-MATHEMATICS Vol.61 No.10(2018):1851-1880.

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