Nonparametric -estimation for right censored regression model with stationary ergodic data

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• 作者：Mohamed Chaouch^a ; ^{mo.chaouch@gmail.com} ; Naâ ; mane Laï ; b^b ; ^c ; Elias Ould Saï ; d^d
• 关键词：60F10 ; 62G07 ; 62F05 ; 62H15
• 刊名：Statistical Methodology
• 出版年：2016
• 出版时间：December 2016
• 年：2016
• 卷：33
• 期：Complete
• 页码：234-255
• 全文大小：616 K
• 卷排序：33

文摘

The present paper deals with a nonparametric MM-estimation for right censored regression model with stationary ergodic data. Defined as an implicit function, a kernel-type estimator of a family of robust regression is considered when the covariate takes its values in RdRd (d≥1d≥1) and the data are sampled from a stationary ergodic process. The strong consistency (with rate) and the asymptotic distribution of the estimator are established under mild assumptions. Moreover, a usable confidence interval is provided which does not depend on any unknown quantity. Our results hold without any mixing condition and do not require the existence of marginal densities. A comparison study based on simulated data is also provided.