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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   +2 more
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Efficient estimation method for generalized ARFIMA models

Communications in Statistics - Theory and Methods, 2022
This paper focuses on pretest and shrinkage estimation strategies for generalized autoregressive fractionally integrated moving average (GARFIMA) models when some of the regression parameters are possible to restrict to a subspace.
S. S. Pandher   +3 more
openaire   +2 more sources

Invariance of the first difference in ARFIMA models

Computational Statistics, 2006
The main goal of the paper is to analyze which estimation method for the fractional parameter is invariant to first-differencing when the model is described by an ARFIMA(p,d,q) process. The authors consider the performance of four estimation methods, belonging to parametric and semiparametric classes, for non-stationary ARFIMA models with main interest
Olbermann, Barbara P.   +2 more
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Another look at the forecast performance of ARFIMA models

International Review of Financial Analysis, 2004
This paper investigates the out-of-sample forecast performance of the autoregressive fractionally integrated moving average [ARFIMA (0,d,0)] specification, both when the underlying value of the fractional differencing parameter (d) is known a priori and when it is unknown.
Ellis, Craig, Wilson, Patrick J.
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Parametric estimation for ARFIMA models via spectral methods

Statistical Methods & Applications, 2005
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
COLI, Mauro   +2 more
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ASSESSING THE PERFORMANCE OF ARIMA AND ARFIMA MODELS IN FORECASTING INTERNALLY GENERATED REVENUE OF KADUNA STATE

FUDMA Journal of Sciences
Internally generated revenue (IGR) is an important source of revenue that can be used to fund public services and infrastructure projects. Accurate forecasting of IGR is essential for effective budgeting and financial planning.
M.I. Usman, T. Musa, Auwalu Ibrahim
semanticscholar   +1 more source

Indirect estimation of ARFIMA and VARFIMA models

Journal of Econometrics, 1999
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Martin, Vance L., Wilkins, Nigel P.
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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   +2 more
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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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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.
openaire   +2 more sources

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