Long-Range Dependence and Sea Level Forecasting

• Κύριοι συγγραφείς: Ercan, Ali (Συγγραφέας), Kavvas, M. Levent (Συγγραφέας), Abbasov, Rovshan K. (Συγγραφέας)
• Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
• Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
• Γλώσσα: English
• Έκδοση: Cham : Springer International Publishing : Imprint: Springer, 2013.
• Σειρά: SpringerBriefs in Statistics,
• Θέματα: Statistics.; Statistical physics.; Dynamical systems.; Climate change.; Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences.; Statistical Physics, Dynamical Systems and Complexity.; Climate Change.

This study shows that the Caspian Sea level time series possess long range dependence even after removing linear trends, based on analyses of the Hurst statistic, the sample autocorrelation functions, and the periodogram of the series. Forecasting performance of ARMA, ARIMA, ARFIMA and Trend Line-AR...

Πίνακας περιεχομένων:

• 1. Introduction
• 2. Long-Range Dependence and ARFIMA Models
• 3. Forecasting, Confidence Band Estimation and Updating
• 4.Case Study I: Caspian Sea Level
• 5.Case Study II: Sea Level Change at Peninsular Malaysia and Sabah-Sarawak
• 6. Summary and Conclusions
• 7. References.