Some simulations and applications of forecasting long-memory time-series models

DOI10.1016/S0378-3758(98)00254-7zbMath0937.62094OpenAlexW1988209856MaRDI QIDQ1304368

Valdério Anselmo Reisen, Sílvia R. C. Lopes

Publication date: 22 September 1999

Published in: Journal of Statistical Planning and Inference (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/s0378-3758(98)00254-7

zbMATH Keywords

fractionallong memoryforecastingperiodogram regressionssmoothed regressions

Mathematics Subject Classification ID

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Cites Work

• Unnamed Item
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• ESTIMATORS FOR LONG-RANGE DEPENDENCE: AN EMPIRICAL STUDY
• REGRESSION OF SPECTRAL ESTIMATORS WITH FRACTIONALLY INTEGRATED TIME SERIES
• THE ESTIMATION AND APPLICATION OF LONG MEMORY TIME SERIES MODELS
• Fractional differencing
• Maximum likelihood identification of Gaussian autoregressive moving average models
• MODELING LONG-MEMORY PROCESSES FOR OPTIMAL LONG-RANGE PREDICTION
• ESTIMATION OF THE FRACTIONAL DIFFERENCE PARAMETER IN THE ARIMA(p, d, q) MODEL USING THE SMOOTHED PERIODOGRAM
• LAG WINDOW ESTIMATION OF THE DEGREE OF DIFFERENCING IN FRACTIONALLY INTEGRATED TIME SERIES MODELS
• Comparing the bias and misspecification in ARFIMA models
• Predictors for Seasonal and Nonseasonal Fractionally Integrated ARIMA Models

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