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Mixed INAR(1) Poisson regression models: Analyzing heterogeneity and serial dependencies in longitudinal count data

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  • Bockenholt, Ulf

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  • Bockenholt, Ulf, 1998. "Mixed INAR(1) Poisson regression models: Analyzing heterogeneity and serial dependencies in longitudinal count data," Journal of Econometrics, Elsevier, vol. 89(1-2), pages 317-338, November.
    • Handle: RePEc:eee:econom:v:89:y:1998:i:1-2:p:317-338
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    8. Rita D. Wheat & Donald G. Morrison, 1990. "Assessing Purchase Timing Models: Whether or Not is Preferable to When," Marketing Science, INFORMS, vol. 9(2), pages 162-170.
    9. Hausman, Jerry & Hall, Bronwyn H & Griliches, Zvi, 1984. "Econometric Models for Count Data with an Application to the Patents-R&D Relationship," Econometrica, Econometric Society, vol. 52(4), pages 909-938, July.
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    14. Morrison, Donald G & Schmittlein, David C, 1988. "Generalizing the NBD Model for Customer Purchases: What Are the Implications and Is It Worth the Effort?," Journal of Business & Economic Statistics, American Statistical Association, vol. 6(2), pages 145-159, April.
    15. Wedel, M, et al, 1993. "A Latent Class Poisson Regression Model for Heterogeneous Count Data," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 8(4), pages 397-411, Oct.-Dec..
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    Cited by:

    1. Fok, Dennis & Paap, Richard & Franses, Philip Hans, 2012. "Modeling dynamic effects of promotion on interpurchase times," Computational Statistics & Data Analysis, Elsevier, vol. 56(11), pages 3055-3069.
    2. Yang Lu & Christian Gourieroux, 2018. "Negative Binomial Autoregressive Process," Working Papers hal-01730050, HAL.
    3. Yang Lu & Christian Gourieroux, 2018. "Negative Binomial Autoregressive Process," CEPN Working Papers 2018-01, Centre d'Economie de l'Université de Paris Nord.

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