NONPARAMETRIC IDENTIFICATION OF NONLINEAR TIME-SERIES - PROJECTIONS

• 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: 10.2307/2291002
• 发表日期: 1994
• 页码: 1398-1409
• 关键词: order determination; models

摘要

We study the possibility of identifying general linear and nonlinear time series models using nonparametric methods. The kernel estimators of the conditional mean and variance are used as a basis, and the properties of these quantities as model indicators are briefly discussed. Some drawbacks are pointed out, and motivated by these we introduce projections as tools of identification. The projections are especially useful for additive modeling. Expressions for the asymptotic bias and variance are obtained. The projection of the conditional variance is suggested as a tool for identifying heteroscedastic time series. The results are illustrated by simulations for both the estimators of the projections and the estimators of the conditional mean and variance.