NONPARAMETRIC IDENTIFICATION OF NONLINEAR TIME-SERIES - SELECTING SIGNIFICANT LAGS

• 成果类型: Article
• 署名作者: TJOSTHEIM, D; AUESTAD, BH
• 署名单位: Universitetet i Stavanger; University of California System; University of California San Diego
• 刊物名称: JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION
• ISSN/ISSBN: 0162-1459
• DOI: 10.2307/2291003
• 发表日期: 1994
• 页码: 1410-1419
• 关键词: order determination; regression; squares; MODEL

摘要

In this article we suggest a nonparametric procedure for selecting significant lags in the model description of a general nonlinear stationary time series. The procedure can be applied to both the conditional mean and the conditional variance and is valid for heteroscedastic series. The procedure is illustrated by simulations and sunspot data, lynx data, and blowfly data are analyzed. It is indicated that projectors can be used in conjunction with the procedure for selecting significant lags to check the adequacy of an additive time series model.