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A geometric time-series model with an alternative dependent Bernoulli counting series

Author

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  • Aleksandar S. Nastić
  • Miroslav M. Ristić
  • Ana V. Miletić Ilić

Abstract

In this article, we first introduce an alternative way for construction of the generalized binomial thinning operator with dependent counting series. Some properties of this thinning operator are derived and discussed. Then, by using this thinning operator, we introduce an integer-valued time-series model with geometric marginals. Some conditional and unconditional properties of this model are derived and discussed. Some estimation methods are considered and for some of them, asymptotic properties of the obtained estimates are derived. Performances of the estimates are discussed through some simulations. Finally, a real data example is considered and the goodness-of-fit of this model is compared with the models based on the binomial, negative binomial, and dependent binomial thinning operators.

Suggested Citation

  • Aleksandar S. Nastić & Miroslav M. Ristić & Ana V. Miletić Ilić, 2017. "A geometric time-series model with an alternative dependent Bernoulli counting series," Communications in Statistics - Theory and Methods, Taylor & Francis Journals, vol. 46(2), pages 770-785, January.
    • Handle: RePEc:taf:lstaxx:v:46:y:2017:i:2:p:770-785
    DOI: 10.1080/03610926.2015.1005100
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    Cited by:

    1. Zeng, Xiaoqiang & Kakizawa, Yoshihide, 2024. "Two-step conditional least squares estimation in ADCINAR(1) process, revisited," Statistics & Probability Letters, Elsevier, vol. 206(C).
    2. Shirozhan, M. & Bakouch, Hassan S. & Mohammadpour, M., 2023. "A flexible INAR(1) time series model with dependent zero-inflated count series and medical contagious cases," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 206(C), pages 216-230.

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