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	Jackknife empirical likelihood for parametric copulas
	Wang, Ruodu ; Peng, Liang ; Yang, Jingping
	2013
关键词	copulas empirical likelihood interval estimation jackknife CONFIDENCE-INTERVALS DISTRIBUTIONS DEPENDENCE
英文摘要	For fitting a parametric copula to multivariate data, a popular way is to employ the so-called pseudo maximum likelihood estimation proposed by Genest, Ghoudi, and Rivest. Although interval estimation can be obtained via estimating the asymptotic covariance of the pseudo maximum likelihood estimation, we propose a jackknife empirical likelihood method to construct confidence regions for the parameters without estimating any additional quantities such as the asymptotic covariance. A simulation study shows the advantages of the new method in case of strong dependence or having more than one parameter involved.; Mathematics, Interdisciplinary Applications; Social Sciences, Mathematical Methods; Statistics & Probability; SCI(E); SSCI; 0; ARTICLE; 5; 325-339; 2013
语种	英语
出处	SCI
内容类型	其他
源URL	[http://hdl.handle.net/20.500.11897/220967]
专题	数学科学学院
推荐引用方式 GB/T 7714	Wang, Ruodu,Peng, Liang,Yang, Jingping. Jackknife empirical likelihood for parametric copulas. 2013-01-01.

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