IDEAS home Printed from https://ideas.repec.org/r/gam/jrisks/v4y2016i1p4-d64467.html
   My bibliography  Save this item

Multivariate Frequency-Severity Regression Models in Insurance

Citations

Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
as


Cited by:

  1. Park, Sojung C. & Kim, Joseph H.T. & Ahn, Jae Youn, 2018. "Does hunger for bonuses drive the dependence between claim frequency and severity?," Insurance: Mathematics and Economics, Elsevier, vol. 83(C), pages 32-46.
  2. Šoltés Erik & Zelinová Silvia & Bilíková Mária, 2019. "General Linear Model: An Effective Tool For Analysis Of Claim Severity In Motor Third Party Liability Insurance," Statistics in Transition New Series, Polish Statistical Association, vol. 20(4), pages 13-31, December.
  3. Minwoo Kim & Himchan Jeong & Dipak Dey, 2022. "Approximation of Zero-Inflated Poisson Credibility Premium via Variational Bayes Approach," Risks, MDPI, vol. 10(3), pages 1-11, March.
  4. Cheung, Eric C.K. & Ni, Weihong & Oh, Rosy & Woo, Jae-Kyung, 2021. "Bayesian credibility under a bivariate prior on the frequency and the severity of claims," Insurance: Mathematics and Economics, Elsevier, vol. 100(C), pages 274-295.
  5. Pechon, Florian & Denuit, Michel & Trufin, Julien, 2018. "Multivariate Modelling of Multiple Guarantees in Motor Insurance of a Household," LIDAM Discussion Papers ISBA 2018019, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
  6. Lu Yang & Claudia Czado, 2022. "Two‐part D‐vine copula models for longitudinal insurance claim data," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 49(4), pages 1534-1561, December.
  7. Youn Ahn, Jae & Jeong, Himchan & Lu, Yang, 2021. "On the ordering of credibility factors," Insurance: Mathematics and Economics, Elsevier, vol. 101(PB), pages 626-638.
  8. Marian Reiff & Erik Šoltés & Silvia Komara & Tatiana Šoltésová & Silvia Zelinová, 2022. "Segmentation and estimation of claim severity in motor third-party liability insurance through contrast analysis," Equilibrium. Quarterly Journal of Economics and Economic Policy, Institute of Economic Research, vol. 17(3), pages 803-842, September.
  9. Eling, Martin & Jung, Kwangmin, 2018. "Copula approaches for modeling cross-sectional dependence of data breach losses," Insurance: Mathematics and Economics, Elsevier, vol. 82(C), pages 167-180.
  10. Kaiwen Wang & Jiehui Ding & Kristen R. Lidwell & Scott Manski & Gee Y. Lee & Emilio Xavier Esposito, 2019. "Treatment Level and Store Level Analyses of Healthcare Data," Risks, MDPI, vol. 7(2), pages 1-22, April.
  11. Gómez-Déniz, E., 2016. "Bivariate credibility bonus–malus premiums distinguishing between two types of claims," Insurance: Mathematics and Economics, Elsevier, vol. 70(C), pages 117-124.
  12. Massimo Costabile & Fabio Viviano, 2021. "Modeling the Future Value Distribution of a Life Insurance Portfolio," Risks, MDPI, vol. 9(10), pages 1-17, October.
  13. Oh, Rosy & Lee, Kyung Suk & Park, Sojung C. & Ahn, Jae Youn, 2020. "Double-counting problem of the bonus–malus system," Insurance: Mathematics and Economics, Elsevier, vol. 93(C), pages 141-155.
  14. Tzougas, George & Jeong, Himchan, 2021. "An expectation-maximization algorithm for the exponential-generalized inverse Gaussian regression model with varying dispersion and shape for modelling the aggregate claim amount," LSE Research Online Documents on Economics 108210, London School of Economics and Political Science, LSE Library.
  15. Erik Šoltés & Silvia Zelinová & Mária Bilíková, 2019. "General Linear Model: An Effective Tool For Analysis Of Claim Severity In Motor Third Party Liability Insurance," Statistics in Transition New Series, Polish Statistical Association, vol. 20(4), pages 13-31, December.
  16. Martin Eling & Kwangmin Jung, 2022. "Heterogeneity in cyber loss severity and its impact on cyber risk measurement," Risk Management, Palgrave Macmillan, vol. 24(4), pages 273-297, December.
  17. Quan Zhiyu & Valdez Emiliano A., 2018. "Predictive analytics of insurance claims using multivariate decision trees," Dependence Modeling, De Gruyter, vol. 6(1), pages 377-407, December.
  18. Fung, Tsz Chai & Badescu, Andrei L. & Lin, X. Sheldon, 2019. "A class of mixture of experts models for general insurance: Theoretical developments," Insurance: Mathematics and Economics, Elsevier, vol. 89(C), pages 111-127.
  19. Yves Staudt & Joël Wagner, 2021. "Assessing the Performance of Random Forests for Modeling Claim Severity in Collision Car Insurance," Risks, MDPI, vol. 9(3), pages 1-28, March.
  20. Bladt, Martin & Yslas, Jorge, 2023. "Robust claim frequency modeling through phase-type mixture-of-experts regression," Insurance: Mathematics and Economics, Elsevier, vol. 111(C), pages 1-22.
  21. George Tzougas & Himchan Jeong, 2021. "An Expectation-Maximization Algorithm for the Exponential-Generalized Inverse Gaussian Regression Model with Varying Dispersion and Shape for Modelling the Aggregate Claim Amount," Risks, MDPI, vol. 9(1), pages 1-17, January.
  22. Verschuren, Robert Matthijs, 2022. "Frequency-severity experience rating based on latent Markovian risk profiles," Insurance: Mathematics and Economics, Elsevier, vol. 107(C), pages 379-392.
  23. Emilio Gómez-Déniz & Enrique Calderín-Ojeda, 2021. "A Priori Ratemaking Selection Using Multivariate Regression Models Allowing Different Coverages in Auto Insurance," Risks, MDPI, vol. 9(7), pages 1-18, July.
  24. Bernard, Carole & Liu, Fangda & Vanduffel, Steven, 2020. "Optimal insurance in the presence of multiple policyholders," Journal of Economic Behavior & Organization, Elsevier, vol. 180(C), pages 638-656.
  25. Oh, Rosy & Lee, Youngju & Zhu, Dan & Ahn, Jae Youn, 2021. "Predictive risk analysis using a collective risk model: Choosing between past frequency and aggregate severity information," Insurance: Mathematics and Economics, Elsevier, vol. 96(C), pages 127-139.
  26. Lee, Gee Y. & Shi, Peng, 2019. "A dependent frequency–severity approach to modeling longitudinal insurance claims," Insurance: Mathematics and Economics, Elsevier, vol. 87(C), pages 115-129.
  27. Chen, Zezhun Chen & Dassios, Angelos & Tzougas, George, 2023. "EM estimation for bivariate mixed poisson INAR(1) claim count regression models with correlated random effects," LSE Research Online Documents on Economics 118826, London School of Economics and Political Science, LSE Library.
  28. Oh, Rosy & Jeong, Himchan & Ahn, Jae Youn & Valdez, Emiliano A., 2021. "A multi-year microlevel collective risk model," Insurance: Mathematics and Economics, Elsevier, vol. 100(C), pages 309-328.
  29. Garrido, J. & Genest, C. & Schulz, J., 2016. "Generalized linear models for dependent frequency and severity of insurance claims," Insurance: Mathematics and Economics, Elsevier, vol. 70(C), pages 205-215.
IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.