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NONPARAMETRIC IDENTIFICATION OF NONLINEAR TIME-SERIES - SELECTING SIGNIFICANT LAGS

被引：70
作者：
TJOSTHEIM, D
AUESTAD, BH
机构：
[1] STAVANGER COLL,DEPT MATH,N-4004 STAVANGER,NORWAY
[2] UNIV CALIF SAN DIEGO,DEPT MATH,SAN DIEGO,CA
来源：
JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION | 1994年 / 89卷 / 428期
关键词：
CONDITIONAL MEAN; CONDITIONAL VARIANCE; FINAL PREDICTION ERROR; LAG STRUCTURE;
D O I：
10.2307/2291003
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：
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.
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页码：1410 / 1419
页数：10
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