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

页码：53 / 77

页数：24

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