Titlebook: Long-Range Dependence and Sea Level Forecasting; Ali Ercan,M. Levent Kavvas,Rovshan K. Abbasov Book 2013 The Author(s) 2013 ARFIMA models.

Autopsy

書目名稱Long-Range Dependence and Sea Level Forecasting影響因子(影響力)




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書目名稱Long-Range Dependence and Sea Level Forecasting被引頻次




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書目名稱Long-Range Dependence and Sea Level Forecasting讀者反饋學(xué)科排名

HACK

似少年

Summary and Conclusion,f Caspian Sea level time series, renders the confidence band estimation and forecast updating components of forecasting quite significant for the forecast performance. In this chapter, a brief summary and conclusions are provided for the monograph “Long-Range Dependence and Sea Level Forecasting”.

FLINT

Long-Range Dependence and ARFIMA Models,In this chapter, long-range dependence concept, Hurst phenomenon and ARFIMA models are introduced and the earlier work on these subjects are reviewed. Several methodologies are introduced for the estimation of long-range dependence index (Hurst number or fractional difference parameter).

acquisition

PANG

Ali Ercan,M. Levent Kavvas,Rovshan K. AbbasovA unique statistical approach to estimate sea level forecasts.Case studies included.Written by experts in the field

EXTOL

mechanism

heckle

Book 2013rst 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

制定法律

Case Study II: Sea Level Change at Peninsular Malaysia and Sabah-Sarawak,el change is estimated in time by assimilating the global mean sea level projections from the AOGCM simulations to the satellite altimeter observations along the subject coastlines. Details of this case study were presented in Ercan et al. (2013) at Hydrol Process, 27(3):367–377.