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Heterogeneity in models of purchase frequency. A comparison of Poisson-gamma mixtures with finite Poisson mixtures

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  • Robert Kapłon

Abstract

Poisson models are fundamental in the modelling of purchase frequencies. However, very often they are statistically incompatible with the data. This stems from the fact that the mean is assumed to be equal to the variance and, in consequence, this fails to capture heterogeneity. Thus Poisson mixture models are often considered instead. The most commonly used of these models is the Poisson-gamma mixture model, which is very often applied to problems in marketing. Hence, it would be advisable to discover its limitations. Using real marketing data sets, we point out the limitations of this approach. Furthermore, we compare it with finite Poisson mixtures.

Suggested Citation

  • Robert Kapłon, 2010. "Heterogeneity in models of purchase frequency. A comparison of Poisson-gamma mixtures with finite Poisson mixtures," Operations Research and Decisions, Wroclaw University of Science and Technology, Faculty of Management, vol. 20(3-4), pages 41-52.
  • Handle: RePEc:wut:journl:v:3-4:y:2010:p:41-52:id:168
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    1. Jie Q. Guo & Pravin K. Trivedi, 2002. "Flexible Parametric Models for Long‐tailed Patent Count Distributions," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 64(1), pages 63-82, February.
    2. Rainer Winkelmann, 2008. "Econometric Analysis of Count Data," Springer Books, Springer, edition 0, number 978-3-540-78389-3, April.
    3. Greene, William, 2008. "Functional forms for the negative binomial model for count data," Economics Letters, Elsevier, vol. 99(3), pages 585-590, June.
    4. 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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