Long-range dependence and sea level forecasting | Perpustakaan Universitas Negeri Jakarta

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Long-range dependence and sea level forecasting

Ercan, Ali - Nama Orang; Kavvas, M. Levent - Nama Orang;

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.

Ketersediaan

Perpustakaan Pusat E727

E727

Tersedia

Informasi Detail

Judul Seri: -
No. Panggil: E727
Penerbit: Swiss : Springer Cham., 2013
Deskripsi Fisik: v, 51 hlm.
Bahasa: English
ISBN/ISSN: -
Klasifikasi: NONE
Tipe Isi: -
Tipe Media: -
Tipe Pembawa: -
Edisi: -
Subjek: Statistika untuk Teknik
Info Detail Spesifik: -
Pernyataan Tanggungjawab: Ali Ercan, M. Levent Kavvas, Rovshan K. Abbasov

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Long-range dependence and sea level forecasting
https://doi.org/10.1007/978-3-319-01505-7

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