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http://dx.doi.org/10.5351/KJAS.2004.17.2.219

Prediction Intervals for Nonlinear Time Series Models Using the Bootstrap Method  

이성덕 (충북대학교 자연과학대학 정보통계학과)
김주성 (충북대학교 자연과학대학 정보통계학과)
Publication Information
The Korean Journal of Applied Statistics / v.17, no.2, 2004 , pp. 219-228 More about this Journal
Abstract
In this paper we construct prediction intervals for nonlinear time series models using the bootstrap. We compare these prediction intervals to traditional asymptotic prediction intervals using quasi-score estimation function and M-quasi-score estimating function comprising bounded functions. Simulation results show that the bootstrap method leads to improved accuracy. The accuracy of the bootstrap is empirically demonstrated with the consumer price index.
Keywords
ARCH models; quasi-score estimating function; bootstrap prediction interval;
Citations & Related Records
Times Cited By KSCI : 1  (Citation Analysis)
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