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Parameter estimation for first-order bifurcating autoregressive processes with Weibull innovations

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  • Zhang, Chenhua

Abstract

We study the first-order bifurcating autoregressive process Xt=ϕX⌊t/2⌋+ϵt with Weibull innovations. Using point process technique, we estimate the model parameter ϕ and the tail index α in the Weibull distribution and obtain the joint limit distribution of estimators.

Suggested Citation

  • Zhang, Chenhua, 2011. "Parameter estimation for first-order bifurcating autoregressive processes with Weibull innovations," Statistics & Probability Letters, Elsevier, vol. 81(12), pages 1961-1969.
    • Handle: RePEc:eee:stapro:v:81:y:2011:i:12:p:1961-1969
    DOI: 10.1016/j.spl.2011.08.014
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    References listed on IDEAS

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    1. Zhou, J. & Basawa, I.V., 2005. "Least-squares estimation for bifurcating autoregressive processes," Statistics & Probability Letters, Elsevier, vol. 74(1), pages 77-88, August.
    2. J. Zhou & I. V. Basawa, 2005. "Maximum Likelihood Estimation for a First‐Order Bifurcating Autoregressive Process with Exponential Errors," Journal of Time Series Analysis, Wiley Blackwell, vol. 26(6), pages 825-842, November.
    3. Davis, Richard A. & McCormick, William P., 1989. "Estimation for first-order autoregressive processes with positive or bounded innovations," Stochastic Processes and their Applications, Elsevier, vol. 31(2), pages 237-250, April.
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