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Sequential estimation of the mean in a random coefficient autoregressive model with beta marginals

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  • Martinsek, Adam T.

Abstract

Random coefficient autoregressive processes with beta marginals provide a useful family of models for data that are both bounded and dependent over time. We obtain results on sample-size efficient sequential estimation of the mean for such processes.

Suggested Citation

  • Martinsek, Adam T., 2001. "Sequential estimation of the mean in a random coefficient autoregressive model with beta marginals," Statistics & Probability Letters, Elsevier, vol. 51(1), pages 53-61, January.
    • Handle: RePEc:eee:stapro:v:51:y:2001:i:1:p:53-61
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    References listed on IDEAS

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    1. Ed McKenzie, 1985. "An Autoregressive Process for Beta Random Variables," Management Science, INFORMS, vol. 31(8), pages 988-997, August.
    2. Fakhrezakeri, I. & Lee, S. Y., 1993. "Sequential Estimation of the Mean Vector of a Multivariate Linear Process," Journal of Multivariate Analysis, Elsevier, vol. 47(2), pages 196-209, November.
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    Cited by:

    1. Martinsek, Adam T., 2002. "Estimation of the maximum and minimum in a model for bounded, dependent data," Statistics & Probability Letters, Elsevier, vol. 56(4), pages 381-393, February.
    2. Panga, Zacarias & Pereira, Luísa, 2019. "On the almost sure convergence for the joint version of maxima and minima of stationary sequences," Statistics & Probability Letters, Elsevier, vol. 154(C), pages 1-1.

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