Volume 6, 2002
New directions in Time Series Analysis (Guest Editor: Philippe Soulier)
Page(s) 239 - 258
Section New directions in Time Series Analysis (Guest Editor: Philippe Soulier)
Published online 15 November 2002
  1. T. Anderson, Goodness of fit tests for spectral distributions. Ann. Statist. 21 (1993) 830-847. [CrossRef] [MathSciNet] [Google Scholar]
  2. J.-M. Bardet, G. Lang, G. Oppenheim, A. Philippe and M. Taqqu, Generators of long-range dependent processes: A survey. Birkhäuser (2002). [Google Scholar]
  3. M. Bartlett, An introduction to stochastic processes. Cambridge University Press (1955). [Google Scholar]
  4. G. Box and D.A. Pierce, Distribution of residual autocorrelations in autoregressive-integrated moving average time series models. J. Am. Stat. Assoc. 65 (1970) 1509-1526. [CrossRef] [Google Scholar]
  5. P. Brockwell and R. Davis, Time Series: Theory and Methods. Springer-Verlag, Springer Ser. in Statistics (1991). [Google Scholar]
  6. W. Chen and R. Deo, A generalized portmanteau goodness-of-fit test for time series models. Preprint (2000). [Google Scholar]
  7. G. Fay, Théorèmes limites pour les fonctionnelles du périodogramme, Ph.D. Thesis. École Nationale Supérieure des Télécommunications (2000). [Google Scholar]
  8. G. Fay, E. Moulines and P. Soulier, Non linear functionals of the periodogram (submitted). [Google Scholar]
  9. G. Fay and P. Soulier, The periodogram of an i.i.d. sequence. Stochastic Process. Appl. 92 (2001) 315-343. [CrossRef] [MathSciNet] [Google Scholar]
  10. R. Fox and M. Taqqu, Large-sample properties of parameter estimates for strongly dependent stationary Gaussian time series. Ann. Statist. 14 (1986) 517-532. [CrossRef] [MathSciNet] [Google Scholar]
  11. L. Giraitis and D. Surgailis, A central limit theorem for quadratic forms in strongly dependent linear variables and its application to asymptotic normality of Whittles's estimate. Probab. Theory Related Fields 86 (1990) 87-104. [Google Scholar]
  12. U. Grenander and M. Rosenblatt, Statistical analysis of stationary time series. Wiley, New York (1957). [Google Scholar]
  13. Y. Hosoya, A limit theory for long-range dependence and statistical inference on related models. Ann. Statist. 25 (1997) 105-137. [CrossRef] [MathSciNet] [Google Scholar]
  14. C. Hurvich, E. Moulines and P. Soulier, The FEXP estimator for potentially non-stationary linear time series. Stochastic Process. Appl. 97 (2002) 307-340. [Google Scholar]
  15. C.W. Hurvich and W. Chen, An efficient taper for potentially overdifferenced long-memory time series. J. Time Ser. Anal. 21 (2000) 155-180. [CrossRef] [MathSciNet] [Google Scholar]
  16. D. Janas and R. von Sachs, Consistency for non-linear functions of the periodogram of tapered data. J. Time Ser. Anal. 16 (1995) 585-606. [CrossRef] [MathSciNet] [Google Scholar]
  17. C. Klueppelberg and T. Mikosch, The integrated periodogram for stable processes. Ann. Statist. 24 (1996) 1855-1879. [CrossRef] [MathSciNet] [Google Scholar]
  18. P. Kokoszka and T. Mikosch, The integrated periodogram for long-memory processes with finite or infinite variance. Stochastic Process. Appl. 66 (1997) 55-78. [CrossRef] [MathSciNet] [Google Scholar]
  19. H. Künsch, Discrimination between monotonic trends and long-range dependence. J. Appl. Probab. 23 (1986) 1025-1030. [CrossRef] [MathSciNet] [Google Scholar]
  20. T. Mikosch and R. Norvaisa, Uniform convergence of the empirical spectral distribution function. Stochastic Process. Appl. 70 (1997) 85-114. [CrossRef] [MathSciNet] [Google Scholar]
  21. A. Mokkadem, Une mesure d'information et son application à des tests pour les processus arma. C. R. Acad. Sci. Paris 319 (1994) 197-200. [Google Scholar]
  22. A. Mokkadem, A measure of information and its applications to test for randomness against ARMA alternatives and to goodness-of-fit test. Stochastic Process. Appl. 72 (1997) 145-159. [Google Scholar]
  23. M. Taniguchi, On estimation of the integrals of certain functions of spectral density. J. Appl. Probab. 17 (1980) 73-83. [CrossRef] [MathSciNet] [Google Scholar]
  24. C. Velasco, Non-stationary log-periodogram regression. J. Econom. 91 (1999) 325-371. [CrossRef] [Google Scholar]
  25. Y. Yajima, Asymptotic properties of estimates in incorrect ARMA models for long-memory time series, in New directions in time series analysis. Part II. Proc. Workshop, Minneapolis/MN (USA) 1990. Springer, New York, IMA Vol. Math. Appl. 46 (1993) 375-382. [Google Scholar]

Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.

Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.

Initial download of the metrics may take a while.