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題名 非平穩時間序列模式選取之研究
Model Selection Concerning Nonstationarity Time Series
作者 廖寶珠
Liao, Pao Chu
貢獻者 鄭天澤
Jeng, Tian Tzer
廖寶珠
Liao, Pao Chu
關鍵詞 非平穩
時間序列
單位根檢定
模式選取
Nonstationarity
Time series
Unit root test
Model selection
日期 1993
上傳時間 29-Apr-2016 16:44:16 (UTC+8)
摘要 時間序列中對於模式階數的選取，一直是重要的課題。從過去文獻研究得知，大多數的討論都局限於平穩的模式。然而近年來，非平穩型序列逐漸成為各學者研究的方向。因此，一個能協助研究者適當處理資料的方法，如採取適當的單位根檢定，是進行實證分析時所必需採行的程序。在本篇文章中我們是採用單位根檢定來決定差分階數，然後再結合 Pukkila etal.(1990)所提出的選模方法決定p、q的階數(簡稱PKK選模法)經由本文模擬結果所得之結論為當序列為平穩型時，直接用PKK選模法來進行階數的選取，能得到較強的選模能力 。但當序列為非平穩型時，則建議先以單位根檢定來決定差分階數，再佐以PKK選模法決定p、q階數。
參考文獻 Agiakloglou, C. and Newbold, P. (1992), "En1pirical Evidence on DickeyFuller
     Tests," ]ouTnal of Ti`me SeTies Analysis, 6, 471-483.
     Box, G. E. P., and Jenkins, G. Nt (1976), Ti`me SeTies Analysis:Forecasting
     and Control, 2nd ed, San Francisco: Holden-Day.
     Choi, B. S. (1992), ARMA 1vlodel Identification) Ne\\v York: Springer Verlag.
     Dickey, D. A., and Said, S. E (1985) , "Hypothesis Testing in ARlj\\;IA(p,l,q)
     l\\iIodels," ] ournal of the A m,erican Statistical Association, 80 , 369-374.
     Dickey, D. A., and Bell, vV, R. and IvIiller, R. B. (1986), "Unit Root in Tin1e
     Series NIodels:Tests and hnplications," The A`meTican Statistician, 40,12-26.
     Dickey, D. A., and Pantula. S. G. (1987) , " Detern1ining the Order of Differencing
     in Autoregressi\\`e Processes," ]o`uTnal of B`ussiness and Econo`mic
     Statistics, 5, 455-461.
     Dickey, D. A., and Fuller, W .A. (1979), "Distribution of the Estilnation for
     Autoregressive Time Series \\.Vith a Unit Root :" ]o`uTnal of the A`merican
     Statistical Association ,74, 427-431.
     --( 1981), "Likelihood Ration Statistics for Autoregressive Tin1e Series
     with A Unit Root," Econo`metTica, 49, 1057-1073.
     Fuller, W. A. (1976), Intorduction to Statistical Time Series, New York:Wiley.
     --(1985), "Nonstationary Autoregressive Time Series ," Handbook of
     Statistics , 5, 1-23.
     Hasza, D. P., and Fuller, W. A. (1979), "Estimation for Autoregressive
     Process with Unit Roots,” The Annals of Statistics, 7, 1106-1120.
     Koreisha,S.,and Pukkila,T.(1990),”A Generalized Least-Squares Approach for Estimation of Autoregressive Moving-Average Models,” Journal of Time Series Analysis, 11, 139-151.
     Koreisha,S.,and Yoshimoto,G.(1991),”A Comparision among Identification Procedures for Autoregressive Moving Average Models,” International Statistical Review, 59, 37-57.
     Pagan, A.R. and Wicken, M.R. (1989), “A Survey of Some Recent Econometric Methods,” The Economic Journal , 962-1025.
     Pantula,S.G.(1989),”Testing for Unit Root in Time Series Data”, Econometric Theory , 5, 256-271.
     Phillips.P.C.B.(1987),”Time Series Regression with Unit Roots,”Econometrica, 55, 277-302.
     Phillips,P.C.B.,and P.Perron. (1988),”Testing for a Unit Root in Time Series Regression.” Biometrika, 75, 335-346.
     Pukkila,T., and Koreisha,S., and Kallinen,A. (1990),”The identification of ARMA Models,” Biometrika, 77, 537-548.
     Pukkila, T.M.,and Krishnaiah,P.R.(1988),”On the Use of Autoregressive Order Determination Criteria in Univariate White Noise Tests,” IEEE Transaction on Acoustics, Speech, and , Signal Processing, 36, 764-774.
     Said,E.D., and Dickey ,D.A. (1984),”Testing for Unit Roots in Autoregressive Moving Avreage Models of Unknow Order,” Biometrika, 71, 599-607.
     Schwert, G.W. (1987),”Effects of Model Specification on Tests for Unit Roots in Macroecomic Data,” Journal of Monetary Economics, 20, 73-103.
     --------(1989), “Tests for Unit Roots: A Monte Carlo Investigation,” Journal of Bussiness and Economic Statistics, 7, 147-159.
     Solo, V.(1984),”The Order of Differencing in ARIMA Models,” Journal of the American Statistical Association, 79, 916-921.
     Wei, Willian W.S. (1990), Time Series Analysis: Univariate and Multivariate Methods,New York:Addison –Wesley.
描述 碩士
國立政治大學
統計學系
G80354020
資料來源 http://thesis.lib.nccu.edu.tw/record/#B2002004204
資料類型 thesis
dc.contributor.advisor 鄭天澤zh_TW
dc.contributor.advisor Jeng, Tian Tzeren_US
dc.contributor.author (Authors) 廖寶珠zh_TW
dc.contributor.author (Authors) Liao, Pao Chuen_US
dc.creator (作者) 廖寶珠zh_TW
dc.creator (作者) Liao, Pao Chuen_US
dc.date (日期) 1993en_US
dc.date.accessioned 29-Apr-2016 16:44:16 (UTC+8)-
dc.date.available 29-Apr-2016 16:44:16 (UTC+8)-
dc.date.issued (上傳時間) 29-Apr-2016 16:44:16 (UTC+8)-
dc.identifier (Other Identifiers) B2002004204en_US
dc.identifier.uri (URI) http://nccur.lib.nccu.edu.tw/handle/140.119/89029-
dc.description (描述) 碩士zh_TW
dc.description (描述) 國立政治大學zh_TW
dc.description (描述) 統計學系zh_TW
dc.description (描述) G80354020zh_TW
dc.description.abstract (摘要) 時間序列中對於模式階數的選取，一直是重要的課題。從過去文獻研究得知，大多數的討論都局限於平穩的模式。然而近年來，非平穩型序列逐漸成為各學者研究的方向。因此，一個能協助研究者適當處理資料的方法，如採取適當的單位根檢定，是進行實證分析時所必需採行的程序。在本篇文章中我們是採用單位根檢定來決定差分階數，然後再結合 Pukkila etal.(1990)所提出的選模方法決定p、q的階數(簡稱PKK選模法)經由本文模擬結果所得之結論為當序列為平穩型時，直接用PKK選模法來進行階數的選取，能得到較強的選模能力 。但當序列為非平穩型時，則建議先以單位根檢定來決定差分階數，再佐以PKK選模法決定p、q階數。zh_TW
dc.description.tableofcontents 第一章　緒論
      1.1　研究動機與目的‧‧‧‧‧‧‧‧‧‧‧‧‧‧‧‧‧‧‧‧‧‧ １
      1.2　文獻探討‧‧‧‧‧‧‧‧‧‧‧‧‧‧‧‧‧‧‧‧‧‧‧‧‧ ２
     
     第二章　差分階數之決定－單位根檢定
      2.1　模式定義‧‧‧‧‧‧‧‧‧‧‧‧‧‧‧‧‧‧‧‧‧‧‧‧‧ ４
      2.2　單位根檢定之理論‧‧‧‧‧‧‧‧‧‧‧‧‧‧‧‧‧‧‧‧‧ ５
     
     第三章　ARIMA模式p、d、q階數之決定
      3.1　PKK選模法‧‧‧‧‧‧‧‧‧‧‧‧‧‧‧‧‧‧‧‧‧‧‧‧１５
      3.2　單位根檢定結合PKK選模法之選模步驟‧‧‧‧‧‧‧‧‧‧‧ １９
     
     第四章　模擬結果分析
      4.1　模擬過程‧‧‧‧‧‧‧‧‧‧‧‧‧‧‧‧‧‧‧‧‧‧‧‧ ２３
      4.2　單位根檢定結合PKK選模法之結果分析‧‧‧‧‧‧‧‧‧‧‧ ２３
      4.3　直接用PKK選模法之結果分析‧‧‧‧‧‧‧‧‧‧‧‧‧‧‧ ３５
      4.4　單位根檢定結合PKK選模法與直接用PKK選模法之結果比較‧‧ ３８
     
     第五章　結論‧‧‧‧‧‧‧‧‧‧‧‧‧‧‧‧‧‧‧‧‧‧‧‧‧‧‧４１
     
     參考文獻‧‧‧‧‧‧‧‧‧‧‧‧‧‧‧‧‧‧‧‧‧‧‧‧‧‧‧‧‧６０		zh_TW
dc.source.uri (資料來源) http://thesis.lib.nccu.edu.tw/record/#B2002004204en_US
dc.subject (關鍵詞) 非平穩zh_TW
dc.subject (關鍵詞) 時間序列zh_TW
dc.subject (關鍵詞) 單位根檢定zh_TW
dc.subject (關鍵詞) 模式選取zh_TW
dc.subject (關鍵詞) Nonstationarityen_US
dc.subject (關鍵詞) Time seriesen_US
dc.subject (關鍵詞) Unit root testen_US
dc.subject (關鍵詞) Model selectionen_US
dc.title (題名) 非平穩時間序列模式選取之研究zh_TW
dc.title (題名) Model Selection Concerning Nonstationarity Time Seriesen_US
dc.type (資料類型) thesisen_US
dc.relation.reference (參考文獻) Agiakloglou, C. and Newbold, P. (1992), "En1pirical Evidence on DickeyFuller
     Tests," ]ouTnal of Ti`me SeTies Analysis, 6, 471-483.
     Box, G. E. P., and Jenkins, G. Nt (1976), Ti`me SeTies Analysis:Forecasting
     and Control, 2nd ed, San Francisco: Holden-Day.
     Choi, B. S. (1992), ARMA 1vlodel Identification) Ne\\v York: Springer Verlag.
     Dickey, D. A., and Said, S. E (1985) , "Hypothesis Testing in ARlj\\;IA(p,l,q)
     l\\iIodels," ] ournal of the A m,erican Statistical Association, 80 , 369-374.
     Dickey, D. A., and Bell, vV, R. and IvIiller, R. B. (1986), "Unit Root in Tin1e
     Series NIodels:Tests and hnplications," The A`meTican Statistician, 40,12-26.
     Dickey, D. A., and Pantula. S. G. (1987) , " Detern1ining the Order of Differencing
     in Autoregressi\\`e Processes," ]o`uTnal of B`ussiness and Econo`mic
     Statistics, 5, 455-461.
     Dickey, D. A., and Fuller, W .A. (1979), "Distribution of the Estilnation for
     Autoregressive Time Series \\.Vith a Unit Root :" ]o`uTnal of the A`merican
     Statistical Association ,74, 427-431.
     --( 1981), "Likelihood Ration Statistics for Autoregressive Tin1e Series
     with A Unit Root," Econo`metTica, 49, 1057-1073.
     Fuller, W. A. (1976), Intorduction to Statistical Time Series, New York:Wiley.
     --(1985), "Nonstationary Autoregressive Time Series ," Handbook of
     Statistics , 5, 1-23.
     Hasza, D. P., and Fuller, W. A. (1979), "Estimation for Autoregressive
     Process with Unit Roots,” The Annals of Statistics, 7, 1106-1120.
     Koreisha,S.,and Pukkila,T.(1990),”A Generalized Least-Squares Approach for Estimation of Autoregressive Moving-Average Models,” Journal of Time Series Analysis, 11, 139-151.
     Koreisha,S.,and Yoshimoto,G.(1991),”A Comparision among Identification Procedures for Autoregressive Moving Average Models,” International Statistical Review, 59, 37-57.
     Pagan, A.R. and Wicken, M.R. (1989), “A Survey of Some Recent Econometric Methods,” The Economic Journal , 962-1025.
     Pantula,S.G.(1989),”Testing for Unit Root in Time Series Data”, Econometric Theory , 5, 256-271.
     Phillips.P.C.B.(1987),”Time Series Regression with Unit Roots,”Econometrica, 55, 277-302.
     Phillips,P.C.B.,and P.Perron. (1988),”Testing for a Unit Root in Time Series Regression.” Biometrika, 75, 335-346.
     Pukkila,T., and Koreisha,S., and Kallinen,A. (1990),”The identification of ARMA Models,” Biometrika, 77, 537-548.
     Pukkila, T.M.,and Krishnaiah,P.R.(1988),”On the Use of Autoregressive Order Determination Criteria in Univariate White Noise Tests,” IEEE Transaction on Acoustics, Speech, and , Signal Processing, 36, 764-774.
     Said,E.D., and Dickey ,D.A. (1984),”Testing for Unit Roots in Autoregressive Moving Avreage Models of Unknow Order,” Biometrika, 71, 599-607.
     Schwert, G.W. (1987),”Effects of Model Specification on Tests for Unit Roots in Macroecomic Data,” Journal of Monetary Economics, 20, 73-103.
     --------(1989), “Tests for Unit Roots: A Monte Carlo Investigation,” Journal of Bussiness and Economic Statistics, 7, 147-159.
     Solo, V.(1984),”The Order of Differencing in ARIMA Models,” Journal of the American Statistical Association, 79, 916-921.
     Wei, Willian W.S. (1990), Time Series Analysis: Univariate and Multivariate Methods,New York:Addison –Wesley.		zh_TW