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Modeling time series of counts with a new class of INAR(1) model

Author

Listed:
  • Wooi Chen Khoo

    (University of Malaya)

  • Seng Huat Ong

    (University of Malaya)

  • Atanu Biswas

    (Indian Statistical Institute)

Abstract

This paper presents a new model for a stationary non-negative first order of integer-valued random variables based on the Pegram and thinning operators. Some fundamental and regression properties of the proposed model are discussed. Maximum likelihood estimation (MLE) by the EM algorithm is applied to estimate the parameters. Numerical studies to compare the proposed model with the thinning and Pegram models and the breakdown point of MLE for the proposed model have been conducted. Finally, a real life count data set has been used to illustrate its application. Comparison with existing models by AIC showed that the proposed model is much better and illustrates its potential usefulness in empirical modeling.

Suggested Citation

  • Wooi Chen Khoo & Seng Huat Ong & Atanu Biswas, 2017. "Modeling time series of counts with a new class of INAR(1) model," Statistical Papers, Springer, vol. 58(2), pages 393-416, June.
    • Handle: RePEc:spr:stpapr:v:58:y:2017:i:2:d:10.1007_s00362-015-0704-0
    DOI: 10.1007/s00362-015-0704-0
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    References listed on IDEAS

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    1. Robert Jung & A. Tremayne, 2011. "Useful models for time series of counts or simply wrong ones?," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 95(1), pages 59-91, March.
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    4. Schweer, Sebastian & Weiß, Christian H., 2014. "Compound Poisson INAR(1) processes: Stochastic properties and testing for overdispersion," Computational Statistics & Data Analysis, Elsevier, vol. 77(C), pages 267-284.
    5. Mátyás Barczy & Márton Ispány & Gyula Pap & Manuel Scotto & Maria Silva, 2012. "Additive outliers in INAR(1) models," Statistical Papers, Springer, vol. 53(4), pages 935-949, November.
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    8. Biswas, Atanu & Song, Peter X.-K., 2009. "Discrete-valued ARMA processes," Statistics & Probability Letters, Elsevier, vol. 79(17), pages 1884-1889, September.
    9. Rong Zhu & Harry Joe, 2006. "Modelling Count Data Time Series with Markov Processes Based on Binomial Thinning," Journal of Time Series Analysis, Wiley Blackwell, vol. 27(5), pages 725-738, September.
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    Cited by:

    1. Wooi Chen Khoo & Seng Huat Ong & Biswas Atanu, 2022. "Coherent Forecasting for a Mixed Integer-Valued Time Series Model," Mathematics, MDPI, vol. 10(16), pages 1-15, August.

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