First-order spatial dependent count integer-valued autoregressive (Sp-DCINAR(1,1)) process

Alireza Ghodsi*, Hassan S. Bakouch, Mahendran Shitan

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review


In this article, we propose a new model to model the spatial count data on a two-dimensional regular grid using binomial thinning operator with dependent Bernoulli counting series. The model is called “first-order spatialdependent count integer-valued autoregressive (Sp-DCINAR(1,1)) model.” Some of its properties have been derived and the estimation of the parameters of the model are obtained by the Yule-Walker method, conditional least squares method and conditional maximum likelihood method. Finally, numerical results are presented together with an application to a two-dimensional practical data set.
Original languageEnglish
Pages (from-to)1-11
Number of pages11
JournalCommunications in Statistics: Simulation and Computation
Early online date18 Jul 2023
Publication statusE-pub ahead of print - 18 Jul 2023


  • 62M10
  • 62M30
  • Dependent Bernoulli counting series
  • Generalized binomial thinning operator
  • Integer-valued time series
  • Simulation
  • Sp-DCINAR(1,1) model

ASJC Scopus subject areas

  • Statistics and Probability
  • Modelling and Simulation


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