Least square estimator of the parameter of AR-ARCH model in the presence of missing data

被引：0

作者：

Hamaz, Abdelghani ^{[1
]}

Altendji, Belkais ^{[2
]}

机构：

[1] Mouloud Mammeri Univ Tizi Ouzou, Lab Pure & Appl Math, Tizi Ouzou, Algeria

[2] Katholieke Univ Leuven, Stat & Risk Management Dept, Leuven, Belgium

来源：

INTERNATIONAL JOURNAL OF APPLIED MATHEMATICS & STATISTICS | 2021年 / 60卷 / 01期

关键词：

AR-ARCH processes; Least square estimation; Missing data; Asymptotic normality; GARCH;

D O I：

暂无

中图分类号：

O29 [应用数学];

学科分类号：

070104 ;

摘要：

In this paper we prove the strong consistency and asymptotic normality of the least square estimator of the parameter of autoregressive models, with the noise sequence driven by a ARCH model, in the presence of missing data. Simulation experiments are presented.

引用

页码：15 / 23

页数：9

共 12 条

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