On a partly linear autoregressive model with moving average errors

被引：1

作者：

Bianco, Ana

Boente, Graciela ^{[1
]}

机构：

[1] Univ Buenos Aires, Fac Ciencias Exactas & Nat, Buenos Aires, DF, Argentina

来源：

JOURNAL OF NONPARAMETRIC STATISTICS | 2010年 / 22卷 / 06期

关键词：

ergodicity; Fisher-consistency; moving average errors; partly linear autoregression; smoothing techniques; DENSITY-ESTIMATION; BANDWIDTH CHOICE; TIME-SERIES;

D O I：

10.1080/10485250903469744

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 paper, we generalise the partly linear autoregression model considered in the literature by including moving average errors when we want to allow a large dependence to the past observations. The strong ergodicity of the process is derived. A consistent procedure to estimate the parametric and nonparametric components is provided together with a test statistic that allows to check the presence of a moving average component in the model. Also, a Monte Carlo study is carried out to check the performance of the given proposals.

引用

页码：797 / 820

页数：24

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