UNIFORM CONSISTENCY FOR NONPARAMETRIC ESTIMATORS IN NULL RECURRENT TIME SERIES

被引：23

作者：

Gao, Jiti ^{[1
]}

Kanaya, Shin ^{[2
]}

Li, Degui ^{[3
]}

Tjostheim, Dag ^{[4
]}

机构：

[1] Monash Univ, Caulfield, Vic 3145, Australia

[2] Univ Aarhus, DK-8000 Aarhus C, Denmark

[3] Univ York, York YO10 5DD, N Yorkshire, England

[4] Univ Bergen, N-5020 Bergen, Norway

来源：

ECONOMETRIC THEORY | 2015年 / 31卷 / 05期

基金：

澳大利亚研究理事会; 新加坡国家研究基金会;

关键词：

REGRESSION ESTIMATION; CONVERGENCE RATES; KERNEL ESTIMATION;

D O I：

10.1017/S0266466614000577

中图分类号：

F [经济];

学科分类号：

02 ;

摘要：

This paper establishes uniform consistency results for nonparametric kernel density and regression estimators when time series regressors concerned are nonstationary null recurrent Markov chains. Under suitable regularity conditions, we derive uniform convergence rates of the estimators. Our results can be viewed as a nonstationary extension of some well-known uniform consistency results for stationary time series.

引用

页码：911 / 952

页数：42

共 38 条

[1] NONPARAMETRIC KERNEL ESTIMATION FOR SEMIPARAMETRIC MODELS [J].