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  • 1
    Online Resource
    Online Resource
    Cham : Springer International Publishing
    UID:
    gbv_1652996923
    Format: Online-Ressource (V, 51 p. 21 illus., 6 illus. in color, online resource)
    ISBN: 9783319015057
    Series Statement: SpringerBriefs in Statistics
    Content: 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.
    Content: 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-ARFIMA (TL-ARFIMA) combination models are investigated. The forecast confidence bands and the forecast updating methodology, provided for ARIMA models in the literature, are modified for the ARFIMA models. Sample autocorrelation functions are utilized to estimate the differencing lengths of the ARFIMA models. The confidence bands of the forecasts are estimated using the probability densities of the residuals without assuming a known distribution. There are no long-term sea level records for the region of Peninsular Malaysia and Malaysia’s Sabah-Sarawak northern region of Borneo Island. In such cases the Global Climate Model (GCM) projections for the 21st century can be downscaled to the Malaysia region by means of regression techniques, utilizing the short records of satellite altimeters in this region against the GCM projections during a mutual observation period. This book will be useful for engineers and researchers working in the areas of applied statistics, climate change, sea level change, time series analysis, applied earth sciences, and nonlinear dynamics.
    Note: Description based upon print version of record , 1. Introduction2. 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.
    Additional Edition: ISBN 9783319015040
    Additional Edition: Erscheint auch als Druck-Ausgabe Ercan, Ali Long-range dependence and sea level forecasting Cham : Springer, 2013 ISBN 9783319015040
    Language: English
    Subjects: Geography
    RVK:
    Keywords: Meeresspiegel ; Prognose ; Mathematisches Modell
    URL: Volltext  (lizenzpflichtig)
    URL: Volltext  (lizenzpflichtig)
    URL: Cover
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