User menu

Accès à distance ? S'identifier sur le proxy UCLouvain

Duration dependence models for claim counts

Primary tabs

Boucher, Jean-Philippe Denuit, Michel [UCL]
Document type Article de périodique (Journal article) – Article de recherche
Publication date 2007
Language Anglais
Journal information "German Actuarial Bulletin" - Vol. 28, p. 29-45 (2007)
Peer reviewed yes
issn 1864-0281
Publication status Publié
Affiliation Louvain School of Management
Links
  1. Abramowitz M,Stegun IA (1968) Handbook of Mathematical Functions, National Bureau of Standards. Applied Mathematics Series 55. Dover, New York
  2. Bates G, Neyman J (1951) Contributions to the theory of accident proneness. II: True or false contagion, University of California Publications in Statistics 215–253
  3. Boyer M, Dionne G, Vanasse C (1992) Econometric Models of Accident Distribution. In: Dionne G (ed) Contributions to Insurance Economics. Kluwer Academic Press, Boston
  4. Bradlow ET, Fader PS, Adrian MT, McShane B (2006) Count models based on Weibull interarrival times, Working Paper
  5. Burnham KP, Anderson DR (2002) Model Selection and Multi-Model Inference: A Practical Information-Theoretic Approach. Springer, New York
  6. Cameron A. Colin, Trivedi Pravin K., Regression Analysis of Count Data, ISBN:9780511814365, 10.1017/cbo9780511814365
  7. Feller W (1943) On a general class of ‘contagious’ distributions. Annals of Mathematical Statistics 14:389–400
  8. Golden RM (2003) Discrepancy risk model selection test theory for comparing possibly misspecified or nonnested models. Psychometrika 68:229–249
  9. Keiding N, Andersen C, Fledelius P (1995) The Cox regression model for claims data in non-life insurance. Astin Bulletin 28:95–118
  10. Lawless JF (1987) Regression methods for Poisson process data. Journal of the American Statistical Association 82:808–815
  11. Lemaire Jean, Bonus-Malus Systems in Automobile Insurance, ISBN:9789401042758, 10.1007/978-94-011-0631-3
  12. Marshall AW, Olkin I (1990) Multivariate distributions generated from mixtures of convolution and product families. In: Block HW, Sampson AR, Savits TH (eds.) Topics in Statistical Dependence, Lecture Notes-Monograph Series, Vol. 16:371–393 Hayward, CA.
  13. Nelson KP, Lipsitz SR, Fitzmaurice GM, Ibrahim J, Parzen M, Strawderman R (2006) Use of the probability integral transformation to fit nonlinear mixed-effects models with nonnormal random effects. Journal of Computational and Graphical Statistics 15:39–57
  14. Pinquet J (2000) Experience rating through heterogeneous models. In: Dionne G (ed.) Handbook of Insurance:459–500 Kluwer Academic, Boston
  15. Rivers D, Vuong Q (2002) Model selection tests for nonlinear dynamic models. Econometrics Journal 5:1–39
  16. Scollnik David P. M., Actuarial Modeling with MCMC and BUGs, 10.1080/10920277.2001.10595987
  17. Smith AFM, Roberts GO (1993) Bayesian computation via the Gibbs sampler and related Markov Chain Monte Carlo methods (with discussion). Journal of the Royal Statistical Society, Series B 55:3–23
  18. Vuong QH (1989) Likelihood ratio tests for model selection and non-nested hypotheses. Econometrica 57:307–333
  19. Winkelmann Rainer, Econometric Analysis of Count Data, ISBN:9783662115916, 10.1007/978-3-540-24728-9
  20. Winkelmann R (1995): Duration dependence and dispersion in count data models. Journal of Business and Economic Statistics 13:467–474
  21. Winkelmann R, Zimmermann KF (1991) A new approach for modeling economic count data. Economics Letters 37:139–143
  22. Winkelmann R, Zimmermann KF (1995) Recent development in count data modelling: Theory and application. Journal of Economic Surveys 9:1–24
Bibliographic reference Boucher, Jean-Philippe ; Denuit, Michel. Duration dependence models for claim counts. In: German Actuarial Bulletin, Vol. 28, p. 29-45 (2007)
Permanent URL http://hdl.handle.net/2078/16876