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Quasi-likelihood inference for self-exciting threshold integer-valued autoregressive processes

Author

Listed:
  • Han Li

    (Jilin University)

  • Kai Yang

    (Jilin University)

  • Dehui Wang

    (Jilin University)

Abstract

This article redefines the self-exciting threshold integer-valued autoregressive (SETINAR(2,1)) processes under a weaker condition that the second moment is finite, and studies the quasi-likelihood inference for the new model. The ergodicity of the new processes is discussed. Quasi-likelihood estimators for the model parameters and the asymptotic properties are obtained. Confidence regions of the parameters based on the quasi-likelihood method are given. A simulation study is conducted for the evaluation of the proposed approach and an application to a real data example is provided.

Suggested Citation

  • 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.
    • Handle: RePEc:spr:compst:v:32:y:2017:i:4:d:10.1007_s00180-017-0748-9
    DOI: 10.1007/s00180-017-0748-9
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    References listed on IDEAS

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    Cited by:

    1. Yang, Kai & Yu, Xinyang & Zhang, Qingqing & Dong, Xiaogang, 2022. "On MCMC sampling in self-exciting integer-valued threshold time series models," Computational Statistics & Data Analysis, Elsevier, vol. 169(C).
    2. Kai Yang & Han Li & Dehui Wang & Chenhui Zhang, 2021. "Random coefficients integer-valued threshold autoregressive processes driven by logistic regression," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 105(4), pages 533-557, December.
    3. Xinyang Wang & Dehui Wang & Kai Yang, 2021. "Integer-valued time series model order shrinkage and selection via penalized quasi-likelihood approach," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 84(5), pages 713-750, July.
    4. Kai Yang & Yao Kang & Dehui Wang & Han Li & Yajing Diao, 2019. "Modeling overdispersed or underdispersed count data with generalized Poisson integer-valued autoregressive processes," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 82(7), pages 863-889, October.
    5. Kai Yang & Yiwei Zhao & Han Li & Dehui Wang, 2023. "On bivariate threshold Poisson integer-valued autoregressive processes," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 86(8), pages 931-963, November.

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