Approximate Asymptotic Variance-Covariance Matrix for the Whittle Estimators of GAR(1) Parameters

被引：6

作者：

Shitan, Mahendran ^{[1
,2
]}

Peiris, Shelton ^{[3
]}

机构：

[1] Univ Putra Malaysia, Dept Math, Serdang 43400, Malaysia

[2] Univ Putra Malaysia, Inst Math Res, Lab Computat Stat & Operat Res, Serdang 43400, Malaysia

[3] Univ Sydney, Sch Math & Stat, Sydney, NSW 2006, Australia

来源：

COMMUNICATIONS IN STATISTICS-THEORY AND METHODS | 2013年 / 42卷 / 05期

关键词：

Asymptotic; Covariance; Generalized Autoregression; Spectral density; Time series; Variance; Whittle's estimation; 62M10;

D O I：

10.1080/03610926.2011.569862

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：

Generalized Autoregressive (GAR) processes have been considered to model some features in time series. The Whittle's estimates have been investigated for the GAR(1) process by a simulation study by Shitan and Peiris (2008). This article derives approximate theoretical expressions for the enteries of the asymptotic variance-covariance matrix for those estimates of GAR(1) parameters. These results are supported by a simulation study.

引用

页码：756 / 770

页数：15

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