Model selection for broadband semiparametric estimation of long memory in time series

Journal of Time Series Analysis

Volumn 22, Issue 6, 2001, Pages 679-709

  Hurvich, Clifford M ^a  

^a NEW YORK UNIVERSITY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

EID: 0012650280     PISSN: 01439782     EISSN: None     Source Type: Journal    
DOI: 10.1111/1467-9892.00248     Document Type: Article

References (25)

1. BERAN, J. (1993) Fitting long-memory models by generalized linear regression. Biometrika 80, 817-22.
2. _ (1994) Statistics for Long-memory Processes. New York: Chapman and Hall.
3. BHANSALI, R. J. (1986) A derivation of the information criteria for selecting autoregressive models. Adv. in Appl. Probab. 18, 360-87.
4. _ and KOKOSZKA, P. S. (1999) Estimation of the long memory parameter by fitting fractional autoregressive models. Preprint.
5. BLOOMFIELD, P. (1973) An exponential model for the spectrum of a scalar time series. Biometrika 60, 217-26.
6. BRODSKY, J. (1997) Parameter estimation, model selection and multi-step forecasting for a long memory time series. Doctoral dissertation, New York University Stern School of Business.
7. DAVIES, R. B. and HARTE, D. S. (1987) Tests for Hurst effect. Biometrika 74, 95-101.
8. FINDLEY, D. F. (1985) On the unbiasedness property of AIC for exact or approximating linear stochastic time series models. J. Time Ser. Anal. 6, 229-52.
9. GEWEKE, J. and PORTER-HUDAK, S. (1983) The estimation and application of long memory time series models. J. Time Ser. Anal. 4, 221-37.
10. HENRY, M. and ROBINSON, P. M. (1996) Bandwidth choice in Gaussian semiparametric estimation of long range dependence. Athens Conference on Applied Probability and Time Series Analysis, Vol. II, 19-46, Lecture Notes in Statistics 115. New York: Springer.
11. HURVICH, C. M. and BELTRAO, K. I. (1994) Automatic semiparametric estimation of the memory parameter of a long memory time series. J. Time Ser. Anal. 15, 285-302.
12. _ and BRODSKY, J. (1997) Broadband semiparametric estimation of the memory parameter of a long-memory time series using fractional exponential models. Working Paper SOR-97-2, New York University Stern School of Business, Department of Statistics and Operations Research.
13. _ and DEO, R. S. (1999) Plug-in selection of the number of frequencies in regression estimates of the memory parameter of a long-memory time series. J. Time Ser. Anal. 20, 331-41.
14. _ and TSAI, C.-L. (1995) Relative rates of convergence for efficient model selection criteria in linear regression. Biometrika 82, 418-25.
15. _, DEO, R. S. and BRODSKY, J. (1998) The mean squared error of Geweke and Porter-Hudak's estimator of the memory parameter of a long memory time series. J. Time Ser. Anal. 19, 19-46.
16. JANACEK, G. J. (1982) Determining the degree of differencing for time series via the log spectrum. J. Time Ser. Anal. 3, 177-83.
17. KUNSCH, H. R. (1987) Statistical aspects of self-similar processes. In Proceedings of the First World Congress of the Bernoulli Society (eds Yu. Prohorov and V. V. Sazanov) 1, 67-74. Utrecht: VNU Science Press.
18. L, cross-validation and generalized cross-validation. Ann. Statist. 15, 958-75.
19. MOULINES, E. and SOULIER, P. (1999) Broad band log-periodogram regression of time series with long range dependence. Ann. Statist. 27, 1415-39.
20. _ (2000) Data-driven order selection for projection estimator of the spectral density of time series with long range dependence. J. Time Ser. Anal. 21, 193-218.
21. ROBINSON, P. M. (1994a) Semiparametric analysis of long-memory time series. Ann. Statist. 22, 515-39.
22. _ (1994b) Time series with strong dependence. Advances in Econometrics, Sixth World Congress, Vol. I, 47-95. Cambridge University Press.
23. _ (1995a) Log-periodogram regression of time series with long range dependence. Ann. Statist. 23, 1048-72.
24. _ (1995b) Gaussian semiparametric estimation of long range dependence. Ann. Statist. 23, 1630-61.
25. SHIBATA, R. (1980) Asymptotically efficient selection of the order of the model for estimating parameters of a linear process. Ann. Statist. 8, 147-64.