Long-range dependence and sea level forecasting
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...
Guardat en:
| Autors principals: | , , |
|---|---|
| Format: | Livre numérique |
| Idioma: | Anglais |
| Publicat: |
Cham :
Springer International Publishing
2013.
Cham : Springer Nature |
| Col·lecció: | SpringerBriefs in Statistics
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| Accés en línia: | Accès sur la plateforme de l'éditeur Accès sur la plateforme Istex Accès Université d'Orléans Accès INSA CVL |
| Nota: |
Archives Springer e-books (Licence nationale) Archives Springer e-books (Licence nationale) |
| Autres localisations: | Voir dans le Sudoc |
| Edition sous un autre format: | • Long-range dependence and sea level forecasting, Ali Ercan, M. Levent Kavvas, Rovshan K. Abbasov, 2013, Cham, Springer, 1 vol. (V-51 p.), Springer briefs in statistics, 978-3-319-01504-0 |
Taula de continguts:
- 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