Outliers in functional autoregressive time series

被引:8
作者
Battaglia, F [1 ]
机构
[1] Univ Roma La Sapienza, Dipartimento Stat Probabil & Stat Applicate, I-00100 Rome, Italy
关键词
additive and innovation outliers; local linear regression; nonlinear models; varying-coefficient models;
D O I
10.1016/j.spl.2005.02.003
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
A method for identifying and estimating outliers in a time series is proposed, based on fitting functional autoregressive models. Both additive and innovation outliers may be defined. A simulation experiment and the analysis of some real data sets suggest that the proposed method is effective both for series following some nonlinear models, such as self-exciting threshold autoregressive or exponential autoregressive, and for linear series generated by autoregressive moving average processes. © 2005 Elsevier B.V. All rights reserved.
引用
收藏
页码:323 / 332
页数:10
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