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Estimation of the autoregressive operator by wavelet packets

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  • Laukaitis, Algirdas
  • Vasilecas, Olegas
  • Laukaitis, Ricardas

Abstract

In this paper, we suggest to use wavelet packet bases as an alternative to the widely used principal component analysis in an estimation of the functional autoregressive processes. By extending the notion of the so-called non-standard form of operators representation, we search for the "best" basis on a criterion of highest correlation between pairs of wavelet packet coefficients.

Suggested Citation

  • Laukaitis, Algirdas & Vasilecas, Olegas & Laukaitis, Ricardas, 2009. "Estimation of the autoregressive operator by wavelet packets," Statistics & Probability Letters, Elsevier, vol. 79(1), pages 38-43, January.
    • Handle: RePEc:eee:stapro:v:79:y:2009:i:1:p:38-43
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    References listed on IDEAS

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    1. 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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