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Generalized Poisson integer-valued autoregressive processes with structural changes

Author

Listed:
  • Chenhui Zhang
  • Dehui Wang
  • Kai Yang
  • Han Li
  • Xiaohong Wang

Abstract

In this paper, we introduce a new first-order generalized Poisson integer-valued autoregressive process, for modeling integer-valued time series exhibiting a piecewise structure and overdispersion. Basic probabilistic and statistical properties of this model are discussed. Conditional least squares and conditional maximum likelihood estimators are derived. The asymptotic properties of the estimators are established. Moreover, two special cases of the process are discussed. Finally, some numerical results of the estimates and a real data example are presented.

Suggested Citation

  • Chenhui Zhang & Dehui Wang & Kai Yang & Han Li & Xiaohong Wang, 2022. "Generalized Poisson integer-valued autoregressive processes with structural changes," Journal of Applied Statistics, Taylor & Francis Journals, vol. 49(11), pages 2717-2739, August.
    • Handle: RePEc:taf:japsta:v:49:y:2022:i:11:p:2717-2739
    DOI: 10.1080/02664763.2021.1915255
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