Computational aspects of maximum likelihood estimation of autoregressive fractionally integrated moving average models
AbstractWe discuss computational aspects of likelihood-based estimation of univariate ARFIMA (p,d,q) models. We show how efficient computation and simulation is feasible, even for large samples. We also discuss the implementation of analytical bias corrections.
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Bibliographic InfoArticle provided by Elsevier in its journal Computational Statistics & Data Analysis.
Volume (Year): 42 (2003)
Issue (Month): 3 (March)
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Web page: http://www.elsevier.com/locate/csda
Other versions of this item:
- Jurgen Doornik & Marius Ooms, 2001. "Computational Aspects of Maximum Likelihood Estimation of Autoregressive Fractionally Integrated Moving Average Models," Economics Series Working Papers 2001-W27, University of Oxford, Department of Economics.
- Jurgen A. Doornik & Marius Ooms, 2001. "Computational Aspects of Maximum Likelihood Estimation of Autoregressive Fractionally Integrated Moving Average Models," Economics Papers 2001-W27, Economics Group, Nuffield College, University of Oxford.
- C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models &bull Diffusion Processes
- C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
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- Koopman, S.J.M. & Shephard, N. & Doornik, J.A., 1998. "Statistical Algorithms for Models in State Space Using SsfPack 2.2," Discussion Paper 1998-141, Tilburg University, Center for Economic Research.
- Ooms, M. & Doornik, J.A., 1999. "Inference and Forecasting for Fractional Autoregressive Integrated Moving Average Models, with an application to US and UK inflation," Econometric Institute Research Papers EI 9947/A, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
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- Chung, Ching-Fan & Baillie, Richard T, 1993. "Small Sample Bias in Conditional Sum-of-Squares Estimators of Fractionally Integrated ARMA Models," Empirical Economics, Springer, vol. 18(4), pages 791-806.
- Offer Lieberman, 2001. "Penalised Maximum Likelihood Estimation for Fractional Guassian Processes," Cowles Foundation Discussion Papers 1348, Cowles Foundation for Research in Economics, Yale University.
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