Data-driven estimation of semiparametric fractional autoregressive models
AbstractIn this paper data-driven algorithms for fitting SEMIFAR models (Beran, 1999) are proposed. The algorithms combine the data-driven estimation of the nonparametric trend and maximum likelihood estimation of the parameters. For selecting the bandwidth, the proposal of Beran and Feng (1999) based on the iterative plug-in idea (Gasser et al., 1991) is used. Asymptotic properties of the proposed algorithms are investigated. A large simulation study illustrates the practical performance of the methods.
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Bibliographic InfoPaper provided by Center of Finance and Econometrics, University of Konstanz in its series CoFE Discussion Paper with number 00-16.
Length: 31 Pages
Date of creation: Jun 2000
Date of revision:
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- Jan Beran & Yuanhua Feng & Sucharita Gosh & Philipp Sibbertsen, 2000.
"On robust local polynomial estimation with long-memory errors,"
CoFE Discussion Paper
00-18, Center of Finance and Econometrics, University of Konstanz.
- Beran, Jan & Feng, Yuanhua & Ghosh, Sucharita & Sibbertsen, Philipp, 2002. "On robust local polynomial estimation with long-memory errors," International Journal of Forecasting, Elsevier, vol. 18(2), pages 227-241.
- Beran, Jan & Feng, Yuanhua & Ghosh, Sucharita & Sibbertsen, Philipp, 2000. "On robust local polynominal estimation with long-memory errors," Technical Reports 2000,35, Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen.
- Jan Beran & Yuanhua.Feng, 2001. "Iterative plug-in algorithms for SEMIFAR models - definition, convergence and asymptotic properties," CoFE Discussion Paper 01-11, Center of Finance and Econometrics, University of Konstanz.
- Jan Beran & Yuanhua Feng, 2002. "Local Polynomial Fitting with Long-Memory, Short-Memory and Antipersistent Errors," Annals of the Institute of Statistical Mathematics, Springer, vol. 54(2), pages 291-311, June.
- Jan Beran & Yuanhua Feng & Siegfried Heiler, 2000. "Modifying the double smoothing bandwidth selector in nonparametric regression," CoFE Discussion Paper 00-37, Center of Finance and Econometrics, University of Konstanz.
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