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Estimation in a bivariate integer-valued autoregressive process

Author

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  • Aleksandar S. Nastić
  • Miroslav M. Ristić
  • Predrag M. Popović

Abstract

A bivariate integer-valued autoregressive time series model is presented. The model structure is based on binomial thinning. The unconditional and conditional first and second moments are considered. Correlation structure of marginal processes is shown to be analogous to the ARMA(2, 1) model. Some estimation methods such as the Yule–Walker and conditional least squares are considered and the asymptotic distributions of the obtained estimators are derived. Comparison between bivariate model with binomial thinning and bivariate model with negative binomial thinning is given.

Suggested Citation

  • Aleksandar S. Nastić & Miroslav M. Ristić & Predrag M. Popović, 2016. "Estimation in a bivariate integer-valued autoregressive process," Communications in Statistics - Theory and Methods, Taylor & Francis Journals, vol. 45(19), pages 5660-5678, October.
    • Handle: RePEc:taf:lstaxx:v:45:y:2016:i:19:p:5660-5678
    DOI: 10.1080/03610926.2014.948203
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    Cited by:

    1. Zezhun Chen & Angelos Dassios & George Tzougas, 2023. "Multivariate mixed Poisson Generalized Inverse Gaussian INAR(1) regression," Computational Statistics, Springer, vol. 38(2), pages 955-977, June.

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