Estimating the innovation distribution in nonparametric autoregression

被引：0
|
作者：
Ursula U. Müller
Anton Schick
Wolfgang Wefelmeyer
机构：
[1] Texas A&M University,Department of Statistics
[2] Binghamton University,Department of Mathematical Sciences
[3] University of Cologne,Mathematical Institute
来源：
Probability Theory and Related Fields | 2009年 / 144卷
关键词：
Residual-based empirical distribution function; Local linear smoother; Bahadur representation; 62M05; 62M10; 62G30;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
We prove a Bahadur representation for a residual-based estimator of the innovation distribution function in a nonparametric autoregressive model. The residuals are based on a local linear smoother for the autoregression function. Our result implies a functional central limit theorem for the residual-based estimator.
引用
收藏
页码：53 / 77
页数：24
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