Methodology for selecting subset autoregressive time series models
學年 80
學期 1
出版（發表）日期 1991-12-01
作品名稱 Methodology for selecting subset autoregressive time series models
作品名稱（其他語言）
著者 虞國興; Yu, Gwo-hsing; Lin, Yow-chang
單位 淡江大學水資源及環境工程學系
出版者
著錄名稱、卷期、頁數 Journal of time series analysis 12(4), p.363-373
摘要 In time series modelling, subset models are often desirable, especially when the data exhibit some form of periodic behaviour with a range of different natural periods in terms of days, weeks, months and years. Recently, Hokstad proposed a method based on personal judgement for selecting the first tentative model to obtain the best subset autoregressive model. The subjective approach adopted in the Hokstad method is a disadvantage in building up a computer program which could automatically select the appropriate model of a given time series. In this paper, we propose overcoming this disadvantage by employing the inverse autocorrelation function to select the first tentative model. In addition to sets of synthetic data, some well-known real series such as the D, E and F series of Box and Jenkins and the Canadian lynx data are analysed to validate the proposed method. The results indicate that the method can successfully detect the true model for a given time series.
關鍵字 Subset autoregressive model;inverse autocorrelation function;Bhansali information criterion
語言 en
ISSN 0143-9782
期刊性質 國外
收錄於
產學合作
通訊作者
審稿制度 否
國別 GBR
公開徵稿
出版型式 ,電子版
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