Results 201 to 210 of about 7,220 (228)

Parametric estimation for ARFIMA models via spectral methods

Statistical Methods & Applications, 2005
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COLI, Mauro, FONTANELLA, Lara, GRANTURCO, Mariagrazia   +2 more
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Preliminary estimation of ARFIMA models

2000
In this article we propose a preliminary estimator for the parameters of an ARFIMA(p,d,q) model. The estimation procedure is based on the search of the element in the class of ARFIMA models closest to the estimated ARMA model which best fits the observed time series.
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A permanent-transitory decomposition for ARFIMA processes

Journal of Statistical Planning and Inference, 2004
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Ariño, Miguel A., Marmol, Francesc
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Optimal prediction with nonstationary ARFIMA model

Journal of Forecasting, 2007
AbstractWe propose two methods to predict nonstationary long‐memory time series. In the first one we estimate the long‐range dependent parameterdby using tapered data; we then take the nonstationary fractional filter to obtain stationary and short‐memory time series.
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Modeling of PMU Data Using ARFIMA Models

2018 Clemson University Power Systems Conference (PSC), 2018
Installing Phasor Measurement Units (PMUs) in the smart grid has played an important role in having more reliable and secure grid. Due to the high sampling rate (50 samples/s), PMU generates massive amount of data compared to the conventional SCADA system.
Laith Shalalfeh, Paul Bogdan, Edmond Jonckheere   +2 more
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Comparison between the FUZZY-ARFIMA model and the Hybrid ARFIMA -FUZZY model with application to agricultural data in the city of Mosul

Statistics, Optimization & Information Computing
In this research, we studied forecasting based on time series data for red onion prices in Nineveh Governorate using model ARFIMA Autoregressive fractionally integrated moving average.
Rehab Talal Ahmed, Omar salim Ibrahim
semanticscholar   +1 more source

Long-Range Dependence and ARFIMA Models

2013
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).
Ali Ercan, M. Levent Kavvas, Rovshan K. Abbasov   +2 more
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Analysing inflation by the fractionally integrated ARFIMA-GARCH model

Journal of Applied Econometrics, 1996
This paper considers the application of long-memory processes to describing inflation for 10 countries. We implement a new procedure to obtain approximate maximum likelihood estimates of an ARFIMA-GARCH process; which is fractionally integrated I(d) with a superimposed stationary ARMA component in its conditional mean.
Baillie, Richard T, Chung, Ching-Fan, Tieslau, Margie A   +2 more
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A Novel Prediction Method for ARFIMA Processes

2011 International Conference on Computational and Information Sciences, 2011
The class of autoregressive fractionally integrated moving average (ARFIMA) model is an important type of long memory processes which are widely used in many fields. In this paper, a novel nonparametric method is proposed to predict ARFIMA processes based on phase space reconstruction theory and multivariate local linear estimator.
Wangyong Lv, Huiqi Wang
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DIFFERENTIAL GEOMETRY OFARFIMAPROCESSES

Communications in Statistics - Theory and Methods, 2001
Autoregressive fractionally integrated moving average (ARFIMA) processes are widely used for modeling time series exhibiting both long-memory and short-memory behavior. Properties of Toeplitz matrices associated with the spectral density functions of Gaussian ARFIMAprocesses are used to compute differential geometric quantities.
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