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    政大機構典藏 > 商學院 > 統計學系 > 期刊論文 >  Item 140.119/18207


    Please use this identifier to cite or link to this item: https://nccur.lib.nccu.edu.tw/handle/140.119/18207


    Title: 雙線性時間序列模式選取方法之比較
    Other Titles: On Comparison of Model Selectio Methods for Bilinear Time Series Models
    Authors: 鄭天澤;劉瑞芝
    Jeng, Tian-Tzer;Liu, Ruey-Chih
    Keywords: 雙線性時間序列模式;模式選取;高斯-賽德迭代法
    Binlinear time series models;Model selection;Gauss-seidel iteration
    Date: 1995-12
    Issue Date: 2008-12-19 14:55:31 (UTC+8)
    Abstract: 在過去二十年中，時間序列分析領域中大多數的論文都在探討線性時間序列模式。然而現實生活中，有很多時間序列顯然並不符合線性假設；因此近十年來有些學者乃致力於非線性時間序列模式之研究，並提出各種假設檢定方法，以判斷資料是否為線性。一旦確定資料為非線性，則更進一步配適合適的非線性時間序列模式。一般而言，非線性時間序列模式有三種：雙線性模式、指數自迴歸模式以及起始自迴歸模式。此三類模式中的雙線性模式，由於其性質與傳統線性模式類似，經常容易混淆，是以本主旨在探討雙線性模式選取的各種方法，並比較其選模能力。我們使用高斯－賽德迭代法估計參數，藉電腦模擬資料來比較Subba Rao and Gabr (1984)選模法、修正PKK選模法、AIC和 BIC等四種方法或準則的選模能力。
    In the past 15 years, there have been a lot of researchers working on model selection problems for bilinear (B L) time series models. Several model selection criteria or methods, such as the Subba Rao`s nested search procedure, AIC and BIC criteria, have been suggested and used in the literature. In this paper, the performance of the above model selection criteria/methods are presented and compared, using simulated data, with the modified PKK procedure we have proposed. It is found that the Subba Rao`s nested search procedure has a better performance on average than do modified PKK procedure, AIC and BIC criteria.
    Relation: 中國統計學報, 33(4),581-601
    Data Type: article
    Appears in Collections:[統計學系] 期刊論文

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