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Best linear prediction for [alpha]-stable random processes

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  • Mohammadi, Mohammad
  • Mohammadpour, Adel

Abstract

The best linear prediction for [alpha]-stable random processes based on some past values is presented. The prediction is the best with respect to a criterion known as stable covariation. The minimum stable covariations can be considered as the smallest error tail probabilities. The predictor obtained is equal to the best linear predictor based on minimization of second-moment error for Gaussian processes.

Suggested Citation

  • Mohammadi, Mohammad & Mohammadpour, Adel, 2009. "Best linear prediction for [alpha]-stable random processes," Statistics & Probability Letters, Elsevier, vol. 79(21), pages 2266-2272, November.
    • Handle: RePEc:eee:stapro:v:79:y:2009:i:21:p:2266-2272
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    References listed on IDEAS

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    1. Cline, Daren B. H. & Brockwell, Peter J., 1985. "Linear prediction of ARMA processes with infinite variance," Stochastic Processes and their Applications, Elsevier, vol. 19(2), pages 281-296, April.
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