Robust estimation for vector autoregressive models

被引：20

作者：

Muler, Nora ^{[1
]}

Yohai, Victor J. ^{[2
,3
]}

机构：

[1] Univ Torcuato di Tella, Dept Matemat, Buenos Aires, DF, Argentina

[2] Univ Buenos Aires, Dept Math, Sch Exact & Nat Sci, RA-1053 Buenos Aires, DF, Argentina

[3] Consejo Nacl Invest Cient & Tecn, RA-1033 Buenos Aires, DF, Argentina

来源：

COMPUTATIONAL STATISTICS & DATA ANALYSIS | 2013年 / 65卷

关键词：

Robust estimators; BMM-estimator; VAR models; MULTIVARIATE TIME-SERIES; HIGH BREAKDOWN-POINT; GARCH MODELS; S-ESTIMATORS; ARMA MODELS; REGRESSION;

D O I：

10.1016/j.csda.2012.02.011

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

A new class of robust estimators for VAR models is introduced. These estimators are an extension to the multivariate case of the MM-estimators based on a bounded innovation propagation AR model. They have a filtering mechanism that avoids the propagation of the effect of one outlier to the residuals of the subsequent periods. Besides, they are consistent and have the same asymptotic normal distribution as regular MM-estimators for VAR models. A Monte Carlo study shows that these estimators compare favorable with respect to other robust ones. (C) 2012 Elsevier B.V. All rights reserved.

引用

页码：68 / 79

页数：12

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