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SAPAN GÖZLEM İLE YAPISAL KIRILMA NOKTASI İLİŞKİSİ VE BUNUN BAYESYEN OTOREGRESİF SÜREÇLE TESPİTİ

Year 2008, Volume: 9 Issue: 2, 146 - 157, 01.07.2008

Abstract

Yapısal kırılma noktası, zaman serilerinde sapan gözlem türlerinden biri olan seviye kayması Level Shift olarak düşünülebilir. Çalışmada sapan gözlem türlerinden özellikle seviye kayması ve Bayesyen otoregresif sürece kısaca değinilmiştir. Bu kapsamda seviye kaymasının Bayesyen otoregresif süreçle de bulunabildiği bir seri üzerinde gösterilmiştir.

References

  • CHEN C., LIU L., (1993). Forecasting time series with outliers. Journal of Forecasting,, Vol.12, No.1, 13-35.ss.
  • CHEN C., TIAO, G.C. (1990). Random level-shift time series models, ARIMA approximations, and level-shift detection. Journal of Business & Economic Statistics, Vol. 8, No.1, 83-97.ss.
  • EKİCİ, O. (2005). Bayesyen regresyon ve WinBUGS ile bir uygulama. Yayımlanmamış Yüksek Lisans Tezi, İstanbul Üniversitesi Sosyal Bilimler Enstitüsü.
  • FRANSES, H.P. (2002). Time series model for business and economic forecasting. Cambridge, Cambridge University Press.
  • GIORDANI, P., KOHN, R., DICK VAN DIJK (2007). A Unified approach to nonlinearity, structural change, and outliers. Journal of Econometrics, Vol. 137, No.1, 112-133.ss.
  • KARLUK, R., TONUS, O., ÇATALBA, N. (1999). Güneydoğu Asya ve Rusya krizi karşısında Türkiye. Prof. Dr. Orhan Oğuz Hatırasına Armağan. İstanbul, Marmara Üniversitesi.
  • KIM, I.M., (1991). Structural change and unit roots. Yayımlanmamış doktora tezi, University of Florida.
  • KOOP, G., POTTER, S., (2000). Nonlinearity, structural breaks or outliers in economic time series?. Nonlinear Econometric Modeling in Time Series Analysis, (Chapter 4), Editörler W. BARNETT, D. HENDRY, S. HYLLEBERG, T. TERASVIRTA, D. TJOSTHEIM ve A. WURTZ, Cambridge, Cambridge University Press.
  • LEDOLTER, J. (1989). The Effect of additive outliers on the forecasts from ARIMA models. International Journal of Forecasting, Vol.5, No.2, 231-240.ss.
  • MADDALA, G.S., KIM, M., (2002). Unit Roots, Cointegration and Structural Change”, Cambridge University Press, 505.s.
  • MARAVALL, A., (2006). An application of the TRAMO-SEATS automatic procedure; direct versus indirect adjustment. Computational Statistics & Data Analysis, Vol.50, No.9, 2167-2190.ss.
  • PERRON, P. (1989). The great crash, the oil price shock, and the unit root hypothesis. Econometrica, Vol.57, No.6, 1361-1401.ss.
  • PERRON, P. (1990). Testing for a unit root in a time series with a changing mean. Journal of Business and Economic Statistics, Vol. 8, No.2, 153-162.ss.
  • TSAY, R.S., (1989). Outliers, level shifts and variance changes in time series. Journal of Forecasting,, Vol.7, No.1, 1-20.ss.
  • TSAY, R.S. (1986). Time series model specification in the presence of outliers. Journal of the American Statistical Association, 81, No.393, 32-141.ss.
  • DPT (Devlet Planlama Teşkilatı), (1999). Erişim adresi : <http://www.dpt.gov.tr/ dptweb/ekutup98/prog99/prog99-2.html>, [Erişim Tarihi: 18.03.2007].
  • TCMB (Türkiye Cumhuriyeti Merkez Bankası). Erişim adresi: http://tcmbf40.tcmb.gov.tr/cbt.html, [Erişim Tarihi: 18.03.2007].
  • TÜSİAD (Türkiye Sanayici ve İş Adamları Derneği), (2001). Erişim adresi : <http:// www.tusiad.org/konj_int.nsf/>, [Erişim Tarihi: 18.03.2007].

THE RELATIONSHIP OF ABERRANT OBSERVATION AND STRUCTURAL BREAK POINT: DETERMINATION WITH BAYESIAN AUTOREGRESSIVE PROCESS

Year 2008, Volume: 9 Issue: 2, 146 - 157, 01.07.2008

Abstract

In time series, structural break point can be considered as Level Shift, one type of aberrant observation. Types of aberrant observations, especially Level Shift, and Bayesian autoregressive process are mentioned in the study. In this extent, the ability of finding Level Shift with Bayesian Autoregressive process is also demonstrated on real data

References

  • CHEN C., LIU L., (1993). Forecasting time series with outliers. Journal of Forecasting,, Vol.12, No.1, 13-35.ss.
  • CHEN C., TIAO, G.C. (1990). Random level-shift time series models, ARIMA approximations, and level-shift detection. Journal of Business & Economic Statistics, Vol. 8, No.1, 83-97.ss.
  • EKİCİ, O. (2005). Bayesyen regresyon ve WinBUGS ile bir uygulama. Yayımlanmamış Yüksek Lisans Tezi, İstanbul Üniversitesi Sosyal Bilimler Enstitüsü.
  • FRANSES, H.P. (2002). Time series model for business and economic forecasting. Cambridge, Cambridge University Press.
  • GIORDANI, P., KOHN, R., DICK VAN DIJK (2007). A Unified approach to nonlinearity, structural change, and outliers. Journal of Econometrics, Vol. 137, No.1, 112-133.ss.
  • KARLUK, R., TONUS, O., ÇATALBA, N. (1999). Güneydoğu Asya ve Rusya krizi karşısında Türkiye. Prof. Dr. Orhan Oğuz Hatırasına Armağan. İstanbul, Marmara Üniversitesi.
  • KIM, I.M., (1991). Structural change and unit roots. Yayımlanmamış doktora tezi, University of Florida.
  • KOOP, G., POTTER, S., (2000). Nonlinearity, structural breaks or outliers in economic time series?. Nonlinear Econometric Modeling in Time Series Analysis, (Chapter 4), Editörler W. BARNETT, D. HENDRY, S. HYLLEBERG, T. TERASVIRTA, D. TJOSTHEIM ve A. WURTZ, Cambridge, Cambridge University Press.
  • LEDOLTER, J. (1989). The Effect of additive outliers on the forecasts from ARIMA models. International Journal of Forecasting, Vol.5, No.2, 231-240.ss.
  • MADDALA, G.S., KIM, M., (2002). Unit Roots, Cointegration and Structural Change”, Cambridge University Press, 505.s.
  • MARAVALL, A., (2006). An application of the TRAMO-SEATS automatic procedure; direct versus indirect adjustment. Computational Statistics & Data Analysis, Vol.50, No.9, 2167-2190.ss.
  • PERRON, P. (1989). The great crash, the oil price shock, and the unit root hypothesis. Econometrica, Vol.57, No.6, 1361-1401.ss.
  • PERRON, P. (1990). Testing for a unit root in a time series with a changing mean. Journal of Business and Economic Statistics, Vol. 8, No.2, 153-162.ss.
  • TSAY, R.S., (1989). Outliers, level shifts and variance changes in time series. Journal of Forecasting,, Vol.7, No.1, 1-20.ss.
  • TSAY, R.S. (1986). Time series model specification in the presence of outliers. Journal of the American Statistical Association, 81, No.393, 32-141.ss.
  • DPT (Devlet Planlama Teşkilatı), (1999). Erişim adresi : <http://www.dpt.gov.tr/ dptweb/ekutup98/prog99/prog99-2.html>, [Erişim Tarihi: 18.03.2007].
  • TCMB (Türkiye Cumhuriyeti Merkez Bankası). Erişim adresi: http://tcmbf40.tcmb.gov.tr/cbt.html, [Erişim Tarihi: 18.03.2007].
  • TÜSİAD (Türkiye Sanayici ve İş Adamları Derneği), (2001). Erişim adresi : <http:// www.tusiad.org/konj_int.nsf/>, [Erişim Tarihi: 18.03.2007].
There are 18 citations in total.

Details

Primary Language Turkish
Journal Section Research Article
Authors

Oya Ekici

Özlem Yorulmaz This is me

Publication Date July 1, 2008
Published in Issue Year 2008 Volume: 9 Issue: 2

Cite

APA Ekici, O., & Yorulmaz, Ö. (2008). SAPAN GÖZLEM İLE YAPISAL KIRILMA NOKTASI İLİŞKİSİ VE BUNUN BAYESYEN OTOREGRESİF SÜREÇLE TESPİTİ. Doğuş Üniversitesi Dergisi, 9(2), 146-157.