Robust estimation of bilinear time series models

被引：11

作者：

Gabr, MM ^{[1
]}

机构：

[1] Kuwait Univ, Fac Sci, Dept Stat & Operat Res, Safat 13060, Kuwait

来源：

COMMUNICATIONS IN STATISTICS-THEORY AND METHODS | 1998年 / 27卷 / 01期

关键词：

bilinear models; robust estimation; additive outliers; generalized M estimates;

D O I：

10.1080/03610929808832649

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：

Outliers in time series seriously affect conventional least squares (LS) procedures badly. We propose to study the problem of fitting a bilinear model to time series data in presence of additive outliers (AO). We investigate a modification of some robustified versions of methods used in linear time series models. A Monte Carlo study is performed to investigate the robustness properties of the proposed class of estimates.

引用

页码：41 / 53

页数：13

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