Autopsy
发表于 2025-3-21 19:09:13
书目名称Long-Range Dependence and Sea Level Forecasting影响因子(影响力)<br> http://impactfactor.cn/if/?ISSN=BK0588548<br><br> <br><br>书目名称Long-Range Dependence and Sea Level Forecasting影响因子(影响力)学科排名<br> http://impactfactor.cn/ifr/?ISSN=BK0588548<br><br> <br><br>书目名称Long-Range Dependence and Sea Level Forecasting网络公开度<br> http://impactfactor.cn/at/?ISSN=BK0588548<br><br> <br><br>书目名称Long-Range Dependence and Sea Level Forecasting网络公开度学科排名<br> http://impactfactor.cn/atr/?ISSN=BK0588548<br><br> <br><br>书目名称Long-Range Dependence and Sea Level Forecasting被引频次<br> http://impactfactor.cn/tc/?ISSN=BK0588548<br><br> <br><br>书目名称Long-Range Dependence and Sea Level Forecasting被引频次学科排名<br> http://impactfactor.cn/tcr/?ISSN=BK0588548<br><br> <br><br>书目名称Long-Range Dependence and Sea Level Forecasting年度引用<br> http://impactfactor.cn/ii/?ISSN=BK0588548<br><br> <br><br>书目名称Long-Range Dependence and Sea Level Forecasting年度引用学科排名<br> http://impactfactor.cn/iir/?ISSN=BK0588548<br><br> <br><br>书目名称Long-Range Dependence and Sea Level Forecasting读者反馈<br> http://impactfactor.cn/5y/?ISSN=BK0588548<br><br> <br><br>书目名称Long-Range Dependence and Sea Level Forecasting读者反馈学科排名<br> http://impactfactor.cn/5yr/?ISSN=BK0588548<br><br> <br><br>
HACK
发表于 2025-3-21 21:06:44
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似少年
发表于 2025-3-22 00:41:06
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
发表于 2025-3-22 05:56:15
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
发表于 2025-3-22 12:16:22
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PANG
发表于 2025-3-22 13:25:19
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
发表于 2025-3-22 18:37:57
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mechanism
发表于 2025-3-22 21:40:53
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heckle
发表于 2025-3-23 01:37:31
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
发表于 2025-3-23 06:29:00
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.