Iterative plug-in algorithms for SEMIFAR models - Definition, convergence, and asymptotic properties

Journal of Computational and Graphical Statistics

Volumn 11, Issue 3, 2002, Pages 690-713

  Beran, Jan ^a   Feng, Yuanhua ^a  

^a UNIVERSITY OF KONSTANZ   (Germany)

Author keywords

Antipersistence; Bandwidth selection; Fractional ARIMA; Long range dependence; Nonparametric regression; Semiparametric models

Indexed keywords

EID: 0036750010     PISSN: 10618600     EISSN: None     Source Type: Journal    
DOI: 10.1198/106186002420     Document Type: Article

References (22)

1. Beran, J. (1994), Statistics for Long-Memory Processes, New York: Chapman & Hall.
2. _ (1995), "Maximum Likelihood of Estimation of the Differencing Parameter for Invertible Short- and Long-Memory Autoregressive Integrated Moving Average Models," Journal of the Royal Statistical Society, Ser. B, 57, 659-672.
3. _ (1999), "SEMIFAR Models-A Semiparametric Framework for Modelling Trends, Long-Range Dependence and Nonstationarity," discussion paper No. 99/16, Center of Finance and Econometrics, University of Konstanz.
4. Beran, J., Bhansali, R.J., and Ocker, D. (1998), "On Unified Model Selection for Stationary and Nonstationary Short- and Long-Memory Autoregressive Processes," Biometrika, 85, 921-934.
5. Beran, J., and Feng, Y. (2000), "Supplement to 'Data-Driven Estimation of Semiparametric Fractional Autoregressive Models'-Detailed Simulation Results," Preprint, University of Konstanz.
6. _ (2002), "Locally Polynomial Fitting With Long-Memory, Short-Memory and Antipersistent Errors," Annals of the Institute of Statistical Mathematics, 54, 291-311.
7. Beran, J., and Ocker, D. (1999), "SEMIFAR Forecasts, With Applications to Foreign Exchange Rates", Journal of Statistical Planning and Inference, 80, 137-153.
8. _ (2001) "Volatility of Stock Market Indices-An Analysis Based on SEMIFAR Models" Journal of Business and Economic Statistics, 19, 103-116.
9. Fan, J., and Gijbels, I. (1995), "Data-Driven Bandwidth Selection in Local Polynomial Fitting: Variable Bandwidth and Spatial Adaptation," Journal of the Royal Statistical Society, Ser. B, 57, 371-394.
10. Feng, Y. (1999), Kernel and Locally Weighted Regression With Application to Time Series Decomposition, Berlin: Verlag.
11. Gasser, T., Kneip, A., and Köhler, W. (1991), "A Flexible and Fast Method for Automatic Smoothing," Journal of the American Statistical Association, 86, 643-652.
12. Gasser, T., and Müller, H.G. (1984), "Estimating Regression Functions and Their Derivatives by the Kernel Method," Scandinavian Journal of Statistics, 11, 171-185.
13. Granger, C.W.J., and Joyeux, R. (1980), An Introduction to Long-Range Time Series Models and Fractional Differencing," Journal of Time Series Analysis, 1, 15-30.
14. Härdle, W., Hall, P., and Marron, J.S. (1992), "Regression Smoothing Parameters That Are Not Far From Their Optimum," Journal of the American Statistical Association, 87, 227-233.
15. Hall, P., and Hart, J.D. (1990), "Nonparametric Regression with Long-Range Dependence," Stochastic Processes and Applications, 36, 339-351.
16. Heiler, S., and Feng, Y. (1998), "A Root n Bandwidth Selector for Nonparametric Regression," Journal of Nonparametric Statistics, 9, 1-21.
17. Herrmann, E., and Gasser, T. (1994), "Iterative Plug-In Algorithm for Bandwidth Selection in Kernel Regression Estimation," preprint, Darmstadt Institute of Technology and University of Zürich.
18. Herrmann, E., Gasser, T., and Kneip, A. (1992), "Choice of Bandwidth for Kernel Regression When Residuals are Correlated," Biometrika, 79, 783-795.
19. Hosking, J.R.M. (1981), "Fractional Differencing," Biometrika, 68, 165-176.
20. Müller, H.G. (1985), "Empirical Bandwidth Choice for Nonparametric Kernel Regression by Means of Pilot Estimators," Statistical Decisions, Supplemental Issue, 2, 193-206.
21. Ray, B.K., and Tsay, R.S. (1997), "Bandwidth Selection for Kernel Regression With Long-Range Dependence," Biometrika, 84, 791-802.
22. Ruppert, D., Sheather, S.J., and Wand, M.P. (1995), "An Effective Bandwidth Selector for Local Least Squares Regression," Journal of the American Statistical Association, 90, 1257-1270.