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On a minimum distance estimate of the period in functional autoregressive processes

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  • Wafaa Benyelles
  • Tahar Mourid

Abstract

We consider a continuous time random process with functional autoregressive representation. We state statistical results on a mean functional estimator determining a minimum distance estimator of the period giving consistency and a limit law stated in Mourid and Benyelles [13]. Then we discuss their performance on numerical simulations and on real data analyzing the cycle of a climatic phenomena.

Suggested Citation

  • Wafaa Benyelles & Tahar Mourid, 2012. "On a minimum distance estimate of the period in functional autoregressive processes," Journal of Applied Statistics, Taylor & Francis Journals, vol. 39(8), pages 1703-1718, February.
    • Handle: RePEc:taf:japsta:v:39:y:2012:i:8:p:1703-1718
    DOI: 10.1080/02664763.2012.668178
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    References listed on IDEAS

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    1. Manteiga, Wenceslao Gonzalez & Vieu, Philippe, 2007. "Statistics for Functional Data," Computational Statistics & Data Analysis, Elsevier, vol. 51(10), pages 4788-4792, June.
    2. Mariano Valderrama, 2007. "An overview to modelling functional data," Computational Statistics, Springer, vol. 22(3), pages 331-334, September.
    3. Antoniadis, Anestis & Sapatinas, Theofanis, 2003. "Wavelet methods for continuous-time prediction using Hilbert-valued autoregressive processes," Journal of Multivariate Analysis, Elsevier, vol. 87(1), pages 133-158, October.
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