User menu

Risk classification for claim counts: A comparative analysis of various zero-inflated mixed Poisson and hurdle models

  1. Andrews D., Econometrica, 56, 135 (1988)
  2. Andrews Donald W. K., Chi-Square Diagnostic Tests for Econometric Models: Theory, 10.2307/1913105
  3. Bates G, University of California Publications in Statistics, 215 (1951)
  4. Besson Par Jean-Luc, Partrat et Christian, Trend et systèmes de Bonus-Malus , 10.2143/ast.22.1.2005124
  5. Boyer M., Contributions to Insurance Economics, xx (1992)
  6. van den Broek Jan, A Score Test for Zero Inflation in a Poisson Distribution, 10.2307/2532959
  7. Cameron A.Colin, Trivedi Pravin K., Regression-based tests for overdispersion in the Poisson model, 10.1016/0304-4076(90)90014-k
  8. Cameron A., Regression Analysis of Count Data (1998)
  9. CHANT D., On asymptotic tests of composite hypotheses in nonstandard conditions, 10.1093/biomet/61.2.291
  10. Chernoff Herman, On the Distribution of the Likelihood Ratio, 10.1214/aoms/1177728725
  11. Consul P., Generalized Poisson Distributions: Properties and Applications (1989)
  12. Dean C. B., Testing for Overdispersion in Poisson and Binomial Regression Models, 10.1080/01621459.1992.10475225
  13. Dean C., Lawless J. F., Willmot G. E., A mixed poisson-inverse-gaussian regression model, 10.2307/3314846
  14. Denuit Michel, A New Distribution of Poisson-Type for the Number of Claims, 10.2143/ast.27.2.542049
  15. Denuit Michel, Lang Stefan, Non-life rate-making with Bayesian GAMs, 10.1016/j.insmatheco.2004.08.001
  16. Dionne Georges, Artís Manuel, Guillén Montserrat, Count data models for a credit scoring system, 10.1016/0927-5398(96)00004-7
  17. DIONNE Georges, VANASSE Charles, A Generalization of Automobile Insurance Rating Models, 10.2143/ast.19.2.2014909
  18. Dionne G., Vanasse C., Automobile insurance ratemaking in the presence of asymmetrical information, 10.1002/jae.3950070204
  19. Gossiaux A. M., Bulletin of the Swiss Association of Actuaries, 87 (1981)
  20. Gourieroux C., Jasiak J., Heterogeneous INAR(1) model with application to car insurance, 10.1016/j.insmatheco.2003.11.005
  21. Gourieroux C., Statistics and Econometric Models (1995)
  22. Gourieroux C., Monfort A., Trognon A., Pseudo Maximum Likelihood Methods: Applications to Poisson Models, 10.2307/1913472
  23. Gourieroux C., Monfort A., Trognon A., Pseudo Maximum Likelihood Methods: Theory, 10.2307/1913471
  24. Grogger J. T., Carson R. T., Models for truncated counts, 10.1002/jae.3950060302
  25. Grootendorst Paul V., A comparison of alternative models of prescription drug utilization, 10.1002/hec.4730040304
  26. Gurmu Shiferaw, Generalized hurdle count data regression models, 10.1016/s0165-1765(97)00295-4
  27. Gurmu Shiferaw, Trivedi Pravin K., Overdispersion tests for truncated Poisson regression models, 10.1016/0304-4076(92)90113-6
  28. Lockhart Richard A., Editor's report, 10.1002/cjs.5550300101
  29. HOLGATE P., The modality of some compound Poisson distributions, 10.1093/biomet/57.3.666
  30. Islam M., Bulletin of the Swiss Association of Actuaries, 85 (1992)
  31. Jorgensen B., The Theory of Dispersion Models (1997)
  32. Klugman S., Loss Models: From Data to Decisions (2004)
  33. Kuha Jouni, AIC and BIC : Comparisons of Assumptions and Performance, 10.1177/0049124103262065
  34. Lambert Diane, Zero-Inflated Poisson Regression, with an Application to Defects in Manufacturing, 10.2307/1269547
  35. Lawless Jerald F., Negative binomial and mixed poisson regression, 10.2307/3314912
  36. Lemaire Jean, Bonus-Malus Systems in Automobile Insurance, ISBN:9789401042758, 10.1007/978-94-011-0631-3
  37. Moran P. A. P., Maximum-likelihood estimation in non-standard conditions, 10.1017/s0305004100050088
  38. Pinquet Jean, Experience Rating through Heterogeneous Models, Handbook of Insurance (2000) ISBN:9780792379119 p.459-500, 10.1007/978-94-010-0642-2_14
  39. Pohlmeier Winfried, Ulrich Volker, An Econometric Model of the Two-Part Decisionmaking Process in the Demand for Health Care, 10.2307/146123
  40. Ridout Martin, Hinde John, DeméAtrio Clarice G. B., A Score Test for Testing a Zero-Inflated Poisson Regression Model Against Zero-Inflated Negative Binomial Alternatives, 10.1111/j.0006-341x.2001.00219.x
  41. Santos Silva João M.C, Windmeijer Frank, Two-part multiple spell models for health care demand, 10.1016/s0304-4076(01)00059-8
  42. Shoukri M., Journal of Data Science, 2, 17 (2004)
  43. Tremblay Luc, Using the Poisson Inverse Gaussian in Bonus-Malus Systems , 10.2143/ast.22.1.2005129
  44. Vuong Quang H., Likelihood Ratio Tests for Model Selection and Non-Nested Hypotheses, 10.2307/1912557
  45. Willmot Gordon E., The Poisson-Inverse Gaussian distribution as an alternative to the negative binomial, 10.1080/03461238.1987.10413823
  46. Winkelmann R., Econometric of Count Data (2003)
  47. Winkelmann Rainer, Zimmermann Klaus F., A new approach for modeling economic count data, 10.1016/0165-1765(91)90122-2
  48. Winkelmann Rainer, Zimmermann Klaus F., RECENT DEVELOPMENTS IN COUNT DATA MODELLING: THEORY AND APPLICATION, 10.1111/j.1467-6419.1995.tb00108.x
  49. Yip Karen C.H., Yau Kelvin K.W., On modeling claim frequency data in general insurance with extra zeros, 10.1016/j.insmatheco.2004.11.002
Bibliographic reference Boucher, Jean-Philippe ; Guillén, Montserrat ; Denuit, Michel. Risk classification for claim counts: A comparative analysis of various zero-inflated mixed Poisson and hurdle models. In: North American Actuarial Journal, Vol. 11, no. 4, p. 110-131 (2007)
Permanent URL