Bootstrap prediction intervals for autoregressive models fitted to non-autoregressive processes

被引：0
|
作者：
Matteo Grigoletto
机构：
[1] Università di Padova,Dipartimento di Scienze Statistiche
来源：
Journal of the Italian Statistical Society | 1998年 / 7卷 / 3期
关键词：
Autoregressive processes; interval forecasts; bootstrap; robustness;
D O I：
10.1007/BF03178936
中图分类号：
学科分类号：
摘要：
The familiar Box and Jenkins method used to build prediction intervals for AR processes neglects the variability due to the estimation of model order and parameters. The purpose of the present paper is to assess the robustness of an approach that takes into account this additional uncertainty when the assumption that the underlying process is AR is not satisfied.
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