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Empirical distribution function for mixing random variables. application in nonparametric hazard estimation

 

作者: P. Sarda,   P. Vieu,  

 

期刊: Statistics  (Taylor Available online 1989)
卷期: Volume 20, issue 4  

页码: 559-571

 

ISSN:0233-1888

 

年代: 1989

 

DOI:10.1080/02331888908802207

 

出版商: Akademie-Verlag

 

关键词: GLIVENKO-CANTELLI theorem;empirical distribution function;hazard function;density;φ;-mixing;kernel estimates

 

数据来源: Taylor

 

摘要:

Let X be a multivariate random variable and (Xn)Na sequence of realisations of X which are not necessarily assumed to be independent. We derive a generalization of GLIVENKO-CANTELLI theorem under a φ-mixing,condition on the sequence (Xn). This result together with an improvement of the uniform rate of convergence on a compact set of density kernel estimate leads to uniform rate of convergence of hazard kernel estimate. This last result is illustrated by means of Monte Carlo experiments

 

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