Nonparametric estimation equations for time series data

被引：11

作者：

Cai, ZW ^{[1
]}

机构：

[1] Univ N Carolina, Dept Math, Charlotte, NC 28223 USA

来源：

STATISTICS & PROBABILITY LETTERS | 2003年 / 62卷 / 04期

基金：

美国国家科学基金会;

关键词：

alpha-mixing; continuous and discrete data; estimation equations; local linear fitting; nonlinear time series; robustness;

D O I：

10.1016/S0167-7152(03)00042-7

中图分类号：

O21 [概率论与数理统计]; C8 [统计学];

学科分类号：

020208 ; 070103 ; 0714 ;

摘要：

In this article, the nonparametric version of estimation equations is investigated, which unifies various statistical methodologies, for both nonlinear discrete and continuous time series data. The weak consistency and asymptotic normality of the resulting estimators are established. Under this general framework, a nonparametric regression estimator can be obtained easily and the asymptotic theory can be derived without going through case-by-case. (C) 2003 Elsevier Science B.V. All rights reserved.

引用

页码：379 / 390

页数：12

共 40 条

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