ROBUST ESTIMATION FOR ARMA MODELS

• 成果类型: Article
• 署名作者: Muler, Nora; Pena, Daniel; Yohai, Victor J.
• 署名单位: Universidad Carlos III de Madrid
• 刊物名称: ANNALS OF STATISTICS
• ISSN/ISSBN: 0090-5364
• DOI: 10.1214/07-AOS570
• 发表日期: 2009
• 页码: 816-840
• 关键词: time-series; infinite variance; outliers; parameters

摘要

This paper introduces a new class of robust estimates for ARMA models. They are M-estimates, but the residuals are computed so the effect of one outlier is limited to the period where it occurs. These estimates are closely related to those based on a robust filter, but they have two important advantages: they are consistent and the asymptotic theory is tractable. We perform a Monte Carlo where we show that these estimates compare favorably with respect to standard M-estimates and to estimates based on a diagnostic procedure.