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左截断相依数据下非参数回归的局部M估计
Local M-estimation of nonparametric regression with left-truncated and dependent data
【摘要】 本文对左截断模型,利用局部多项式的方法构造了非参数回归函数的局部M估计.在观察样本为平稳α-混合序列下,建立了该估计量的强弱相合性以及渐近正态性.模拟研究显示回归函数的局部M估计比Nadaraya-Watson型估计和局部多项式估计更稳健.
【Abstract】 In this paper,we construct a local M-estimator of nonparametric regression function by using the local polynomial technique for a left truncated model.We establish weak and strong consistency as well as asymptotic normality of the estimator when the observations form a stationary α-mixing sequence.Simulation study shows that the local M-estimator not only has advantages over the Nadaraya-Watson (NW) type and local polynomial (LP) estimators of the regression function,but also overcomes the lack of robustness for the NW type and LP estimators.
【关键词】 局部M估计;
渐近正态性;
相合性;
左截断;
α-混合序列;
【Key words】 local M-estimator; local polynomial; asymptotic normality; consistency; truncated data; αmixing;
【Key words】 local M-estimator; local polynomial; asymptotic normality; consistency; truncated data; αmixing;
【基金】 国家自然科学基金(批准号:10871146,11271286和11001070);中国博士后科学基金(批准号:2011M500809);安徽省高校自然科学基金重点项目(批准号:KJ2011A032);安徽省自然科学基金(批准号:1208085QA04)资助项目
- 【文献出处】 中国科学:数学 ,Scientia Sinica(Mathematica) , 编辑部邮箱 ,2012年10期
- 【分类号】O212.1
- 【被引频次】7
- 【下载频次】160