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Actuarial statistics with generalized linear mixed models

Citations

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Cited by:

  1. Katrien Antonio & Jan Beirlant, 2008. "Issues in Claims Reserving and Credibility: A Semiparametric Approach With Mixed Models," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 75(3), pages 643-676, September.
  2. Gigante, Patrizia & Picech, Liviana & Sigalotti, Luciano, 2013. "Claims reserving in the hierarchical generalized linear model framework," Insurance: Mathematics and Economics, Elsevier, vol. 52(2), pages 381-390.
  3. Meyricke, Ramona & Sherris, Michael, 2013. "The determinants of mortality heterogeneity and implications for pricing annuities," Insurance: Mathematics and Economics, Elsevier, vol. 53(2), pages 379-387.
  4. Norbert Paska, 2018. "Zastosowanie modeli ZINB GLMM z efektem losowym agenta w taryfikacji ubezpieczeń majątkowych," Collegium of Economic Analysis Annals, Warsaw School of Economics, Collegium of Economic Analysis, issue 53, pages 63-76.
  5. Michal Gerthofer & Michal Pešta, 2017. "Stochastic Claims Reserving in Insurance Using Random Effects," Prague Economic Papers, Prague University of Economics and Business, vol. 2017(5), pages 542-560.
  6. Xie, Liang & Madden, Laurence V., 2014. "%HPGLIMMIX: A High-Performance SAS Macro for GLMM Estimation," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 58(i08).
  7. Katrien Antonio & Emiliano Valdez, 2012. "Statistical concepts of a priori and a posteriori risk classification in insurance," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 96(2), pages 187-224, June.
  8. Li-Hua Lai, 2016. "Dynamic modelling in loss frequency and severity estimated: Evidence from the agricultural rice loss due to typhoons in Taiwan," Agricultural Economics, Czech Academy of Agricultural Sciences, vol. 62(3), pages 113-123.
  9. Pešta, Michal & Okhrin, Ostap, 2014. "Conditional least squares and copulae in claims reserving for a single line of business," Insurance: Mathematics and Economics, Elsevier, vol. 56(C), pages 28-37.
  10. Shengkun Xie & Chong Gan, 2023. "Estimating Territory Risk Relativity Using Generalized Linear Mixed Models and Fuzzy C -Means Clustering," Risks, MDPI, vol. 11(6), pages 1-20, May.
  11. Silvie Kafková & Lenka Křivánková, 2014. "Generalized Linear Models in Vehicle Insurance," Acta Universitatis Agriculturae et Silviculturae Mendelianae Brunensis, Mendel University Press, vol. 62(2), pages 383-388.
  12. Baumgartner, Carolin & Gruber, Lutz F. & Czado, Claudia, 2015. "Bayesian total loss estimation using shared random effects," Insurance: Mathematics and Economics, Elsevier, vol. 62(C), pages 194-201.
  13. Mahani, Alireza S. & Sharabiani, Mansour T.A., 2015. "SIMD parallel MCMC sampling with applications for big-data Bayesian analytics," Computational Statistics & Data Analysis, Elsevier, vol. 88(C), pages 75-99.
  14. Murwan H. M. A. Siddig, 2016. "Application of the Generalized Linear Models in Actuarial Framework," Papers 1611.02556, arXiv.org.
  15. Alicja Wolny-Dominiak & Tomasz Żądło, 2021. "The Measures of Accuracy of Claim Frequency Credibility Predictor," Sustainability, MDPI, vol. 13(21), pages 1-13, October.
  16. Pitselis, Georgios & Grigoriadou, Vasiliki & Badounas, Ioannis, 2015. "Robust loss reserving in a log-linear model," Insurance: Mathematics and Economics, Elsevier, vol. 64(C), pages 14-27.
  17. Fabienne Comte & Celine Duval & Valentine Genon-Catalot & Johanna Kappus, 2015. "Estimation of the Jump Size Density in a Mixed Compound Poisson Process," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 42(4), pages 1023-1044, December.
  18. Hudecová, Šárka & Pešta, Michal, 2013. "Modeling dependencies in claims reserving with GEE," Insurance: Mathematics and Economics, Elsevier, vol. 53(3), pages 786-794.
  19. Michal Gerthofer & Michal Pešta, . "Stochastic Claims Reserving in Insurance Using Random Effects," Prague Economic Papers, University of Economics, Prague, vol. 0, pages 1-19.
  20. Benjamin Avanzi & Greg Taylor & Melantha Wang & Bernard Wong, 2023. "Machine Learning with High-Cardinality Categorical Features in Actuarial Applications," Papers 2301.12710, arXiv.org.
  21. Paulsen, Jostein & Lunde, Astrid & Skaug, Hans Julius, 2008. "Fitting mixed-effects models when data are left truncated," Insurance: Mathematics and Economics, Elsevier, vol. 43(1), pages 121-133, August.
  22. Dietsch, Michel & Petey, Joël, 2015. "The credit-risk implications of home ownership promotion: The effects of public subsidies and adjustable-rate loans," Journal of Housing Economics, Elsevier, vol. 28(C), pages 103-120.
  23. Pigeon, Mathieu & Henry de Frahan, Bruno & Denuit, Michel, 2014. "Evaluation of the EU Proposed Farm Income Stabilisation Tool by Skew Normal Linear Mixed Models," LIDAM Discussion Papers ISBA 2014003, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
  24. Eguchi, Shoichi, 2018. "Model comparison for generalized linear models with dependent observations," Econometrics and Statistics, Elsevier, vol. 5(C), pages 171-188.
  25. Dornheim, Harald & Brazauskas, Vytaras, 2011. "Robust-efficient credibility models with heavy-tailed claims: A mixed linear models perspective," Insurance: Mathematics and Economics, Elsevier, vol. 48(1), pages 72-84, January.
  26. Meng Sun & Yi Lu, 2022. "A Generalized Linear Mixed Model for Data Breaches and Its Application in Cyber Insurance," Risks, MDPI, vol. 10(12), pages 1-23, November.
  27. Andreas Bayerstadler & Franz Benstetter & Christian Heumann & Fabian Winter, 2014. "A predictive modeling approach to increasing the economic effectiveness of disease management programs," Health Care Management Science, Springer, vol. 17(3), pages 284-301, September.
  28. Jan R. Landwehr & Andreas Herrmann & Mark Heitmann, 2009. "To be different or to be average? [Die Attraktivität des Durchschnittsprodukts]," Schmalenbach Journal of Business Research, Springer, vol. 61(3), pages 226-250, May.
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