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Continuous-time fractional ARMA processes

Author

Listed:
  • Viano, M. C.
  • Deniau, C.
  • Oppenheim, G.

Abstract

The field of discrete-time fractional ARMA processes is now of longstanding interest. However, to the best of the author's knowledge, continuous time fractional ARMA processes have not yet been defined. This paper defines such a family, and proves several probabilistic results concerning the memory of these processes and the regularity properties of their sample functions.

Suggested Citation

  • Viano, M. C. & Deniau, C. & Oppenheim, G., 1994. "Continuous-time fractional ARMA processes," Statistics & Probability Letters, Elsevier, vol. 21(4), pages 323-336, November.
    • Handle: RePEc:eee:stapro:v:21:y:1994:i:4:p:323-336
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    Citations

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    Cited by:

    1. Gao, Jiti & Anh, Vo & Heyde, Chris, 2002. "Statistical estimation of nonstationary Gaussian processes with long-range dependence and intermittency," Stochastic Processes and their Applications, Elsevier, vol. 99(2), pages 295-321, June.
    2. Georges Oppenheim & Marie‐Claude Viano, 2004. "Aggregation of random parameters Ornstein‐Uhlenbeck or AR processes: some convergence results," Journal of Time Series Analysis, Wiley Blackwell, vol. 25(3), pages 335-350, May.
    3. M. C. Viano & Cl. Deniau & G. Oppenheim, 1995. "Long‐Range Dependence And Mixing For Discrete Time Fractional Processes," Journal of Time Series Analysis, Wiley Blackwell, vol. 16(3), pages 323-338, May.
    4. Gao, Jiti, 2007. "Nonlinear time series: semiparametric and nonparametric methods," MPRA Paper 39563, University Library of Munich, Germany, revised 01 Sep 2007.
    5. Anne Philippe & Caroline Robet & Marie-Claude Viano, 2021. "Random discretization of stationary continuous time processes," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 84(3), pages 375-400, April.

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