Estimation in a class of nonlinear heteroscedastic time series models

被引：11

作者：

Ngatchou-Wandji, Joseph ^{[1
]}

机构：

[1] Univ Caen, Lab Math Nicolas Oresme, CNRS UMR 6139, F-14032 Caen, France

来源：

ELECTRONIC JOURNAL OF STATISTICS | 2008年 / 2卷

关键词：

Conditional least-squares estimation; Conditional likelihood estimation; Heteroscedastic models; Kernel density estimation; LATEX; 2; epsilon;

D O I：

10.1214/07-EJS157

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：

Parameter estimation in a class of heteroscedastic time series models is investigated. The existence of conditional least-squares and conditional likelihood estimators is proved. Their consistency and their asymptotic normality are established. Kernel estimators of the noise's density and its derivatives are defined and shown to be uniformly consistent. A simulation experiment conducted shows that the estimators perform well for large sample size.

引用

页码：40 / 62

页数：23

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