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First-order observation-driven integer-valued autoregressive processes

Author

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  • Zheng, Haitao
  • Basawa, Ishwar V.

Abstract

A first-order observation-driven integer-valued autoregressive model is introduced. Ergodicity of the process is established. Conditional least squares and maximum likelihood estimators of the model parameters are derived. The performances of these estimators are compared via simulation. The models are applied to a real data set.

Suggested Citation

  • Zheng, Haitao & Basawa, Ishwar V., 2008. "First-order observation-driven integer-valued autoregressive processes," Statistics & Probability Letters, Elsevier, vol. 78(1), pages 1-9, January.
    • Handle: RePEc:eee:stapro:v:78:y:2008:i:1:p:1-9
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    References listed on IDEAS

    as
    1. Fukasawa, T. & Basawa, I. V., 2002. "Estimation for a class of generalized state-space time series models," Statistics & Probability Letters, Elsevier, vol. 60(4), pages 459-473, December.
    2. Haitao Zheng & Ishwar V. Basawa & Somnath Datta, 2006. "Inference for pth‐order random coefficient integer‐valued autoregressive processes," Journal of Time Series Analysis, Wiley Blackwell, vol. 27(3), pages 411-440, May.
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    Cited by:

    1. Yousung Park & Hee-Young Kim, 2012. "Diagnostic checks for integer-valued autoregressive models using expected residuals," Statistical Papers, Springer, vol. 53(4), pages 951-970, November.
    2. Han Li & Kai Yang & Dehui Wang, 2017. "Quasi-likelihood inference for self-exciting threshold integer-valued autoregressive processes," Computational Statistics, Springer, vol. 32(4), pages 1597-1620, December.
    3. Zheqi Wang & Dehui Wang & Jianhua Cheng, 2023. "A new autoregressive process driven by explanatory variables and past observations: an application to PM 2.5," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 32(2), pages 619-658, June.

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