IDEAS home Printed from https://ideas.repec.org/r/cup/cbooks/9780521879149.html
   My bibliography  Save this item

Generalized Linear Models for Insurance Data

Citations

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


Cited by:

  1. Zewei Lin & Dungang Liu, 2022. "Model diagnostics of discrete data regression: a unifying framework using functional residuals," Papers 2207.04299, arXiv.org.
  2. 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.
  3. Thomas Grochtdreis & Susanne Röhr & Franziska U. Jung & Michaela Nagl & Anna Renner & Anette Kersting & Steffi G. Riedel-Heller & Hans-Helmut König & Judith Dams, 2021. "Health Care Services Utilization and Health-Related Quality of Life of Syrian Refugees with Post-Traumatic Stress Symptoms in Germany (the Sanadak Trial)," IJERPH, MDPI, vol. 18(7), pages 1-13, March.
  4. 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.
  5. Yang Lu, 2019. "Flexible (panel) regression models for bivariate count–continuous data with an insurance application," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 182(4), pages 1503-1521, October.
  6. Tzougas, George & Yik, Woo Hee & Mustaqeem, Muhammad Waqar, 2019. "Insurance ratemaking using the Exponential-Lognormal regression model," LSE Research Online Documents on Economics 101729, London School of Economics and Political Science, LSE Library.
  7. Roel Verbelen & Katrien Antonio & Gerda Claeskens, 2018. "Unravelling the predictive power of telematics data in car insurance pricing," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 67(5), pages 1275-1304, November.
  8. Shi, Peng & Feng, Xiaoping & Ivantsova, Anastasia, 2015. "Dependent frequency–severity modeling of insurance claims," Insurance: Mathematics and Economics, Elsevier, vol. 64(C), pages 417-428.
  9. Freek Holvoet & Katrien Antonio & Roel Henckaerts, 2023. "Neural networks for insurance pricing with frequency and severity data: a benchmark study from data preprocessing to technical tariff," Papers 2310.12671, arXiv.org, revised Aug 2024.
  10. Avanzi, Benjamin & Taylor, Greg & Wong, Bernard & Yang, Xinda, 2021. "On the modelling of multivariate counts with Cox processes and dependent shot noise intensities," Insurance: Mathematics and Economics, Elsevier, vol. 99(C), pages 9-24.
  11. Leonardo Costa & Adrian Pizzinga, 2020. "State‐space models for predicting IBNR reserve in row‐wise ordered runoff triangles: Calendar year IBNR reserves & tail effects," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(3), pages 438-448, April.
  12. Shengkun Xie & Anna T. Lawniczak, 2018. "Estimating Major Risk Factor Relativities in Rate Filings Using Generalized Linear Models," IJFS, MDPI, vol. 6(4), pages 1-14, October.
  13. Liivika Tee & Meelis Käärik & Rauno Viin, 2017. "On Comparison of Stochastic Reserving Methods with Bootstrapping," Risks, MDPI, vol. 5(1), pages 1-21, January.
  14. Ana Preda & Gheorghe Matei & Lorand Bogdanffy, 2016. "The Prognosis of the Main Indicators for Sizing the Global Insurance Market," Annals of the University of Petrosani, Economics, University of Petrosani, Romania, vol. 16(2), pages 101-108.
  15. Shrestha, Prabal & Arslan-Ayaydin, Özgür & Thewissen, James & Torsin, Wouter, 2021. "Institutions, regulations and initial coin offerings: An international perspective," International Review of Economics & Finance, Elsevier, vol. 72(C), pages 102-120.
  16. Deepesh Bhati & Enrique Calderín-Ojeda & Mareeswaran Meenakshi, 2019. "A New Heavy Tailed Class of Distributions Which Includes the Pareto," Risks, MDPI, vol. 7(4), pages 1-17, September.
  17. Francis Duval & Mathieu Pigeon, 2019. "Individual Loss Reserving Using a Gradient Boosting-Based Approach," Risks, MDPI, vol. 7(3), pages 1-18, July.
  18. Carlos A. Cardozo & Gilberto A. Paula & Luiz H. Vanegas, 2022. "Generalized log-gamma additive partial linear models with P-spline smoothing," Statistical Papers, Springer, vol. 63(6), pages 1953-1978, December.
  19. 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.
  20. Chenglong Ye & Lin Zhang & Mingxuan Han & Yanjia Yu & Bingxin Zhao & Yuhong Yang, 2022. "Combining Predictions of Auto Insurance Claims," Econometrics, MDPI, vol. 10(2), pages 1-15, April.
  21. Thomas Grochtdreis & Judith Dams & Hans-Helmut König & Alexander Konnopka, 2019. "Health-related quality of life measured with the EQ-5D-5L: estimation of normative index values based on a representative German population sample and value set," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 20(6), pages 933-944, August.
  22. Tzougas, George & Hoon, W. L. & Lim, J. M., 2019. "The negative binomial-inverse Gaussian regression model with an application to insurance ratemaking," LSE Research Online Documents on Economics 101728, London School of Economics and Political Science, LSE Library.
  23. George Tzougas, 2020. "EM Estimation for the Poisson-Inverse Gamma Regression Model with Varying Dispersion: An Application to Insurance Ratemaking," Risks, MDPI, vol. 8(3), pages 1-23, September.
  24. Fuzi, Mohd Fadzli Mohd & Jemain, Abdul Aziz & Ismail, Noriszura, 2016. "Bayesian quantile regression model for claim count data," Insurance: Mathematics and Economics, Elsevier, vol. 66(C), pages 124-137.
  25. Murwan H. M. A. Siddig, 2016. "Application of the Generalized Linear Models in Actuarial Framework," Papers 1611.02556, arXiv.org.
  26. Edward W. Frees & Gee Lee & Lu Yang, 2016. "Multivariate Frequency-Severity Regression Models in Insurance," Risks, MDPI, vol. 4(1), pages 1-36, February.
  27. 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.
  28. Zuleyka Díaz Martínez & José Fernández Menéndez & Luis Javier García Villalba, 2023. "Tariff Analysis in Automobile Insurance: Is It Time to Switch from Generalized Linear Models to Generalized Additive Models?," Mathematics, MDPI, vol. 11(18), pages 1-16, September.
  29. Peng Shi & Glenn M. Fung & Daniel Dickinson, 2022. "Assessing hail risk for property insurers with a dependent marked point process," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 185(1), pages 302-328, January.
  30. Aivars Spilbergs & Andris Fomins & Māris Krastiņš, 2022. "Multivariate Modelling of Motor Third Party Liability Insurance Claims," European Journal of Business Science and Technology, Mendel University in Brno, Faculty of Business and Economics, vol. 8(1), pages 5-18.
  31. Shi, Peng & Zhao, Zifeng, 2024. "Enhanced pricing and management of bundled insurance risks with dependence-aware prediction using pair copula construction," Journal of Econometrics, Elsevier, vol. 240(1).
  32. Jiří Valecký, 2016. "Modelling Claim Frequency in Vehicle Insurance," Acta Universitatis Agriculturae et Silviculturae Mendelianae Brunensis, Mendel University Press, vol. 64(2), pages 683-689.
  33. 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.
  34. Barbara Guardabascio & Marco Ventura, 2013. "Estimating the dose-response function through the GLM approach," German Stata Users' Group Meetings 2013 10, Stata Users Group.
  35. Emilio Gómez-Déniz & Enrique Calderín-Ojeda, 2018. "Multivariate Credibility in Bonus-Malus Systems Distinguishing between Different Types of Claims," Risks, MDPI, vol. 6(2), pages 1-11, April.
  36. Deprez, Laurens & Antonio, Katrien & Boute, Robert, 2021. "Pricing service maintenance contracts using predictive analytics," European Journal of Operational Research, Elsevier, vol. 290(2), pages 530-545.
  37. Richardson, Robert & Hartman, Brian, 2018. "Bayesian nonparametric regression models for modeling and predicting healthcare claims," Insurance: Mathematics and Economics, Elsevier, vol. 83(C), pages 1-8.
  38. Yves L. Grize, 2015. "Applications of Statistics in the Field of General Insurance: An Overview," International Statistical Review, International Statistical Institute, vol. 83(1), pages 135-159, April.
  39. Jiří Valecký, 2017. "Calculation of Solvency Capital Requirements for Non-life Underwriting Risk Using Generalized Linear Models," Prague Economic Papers, Prague University of Economics and Business, vol. 2017(4), pages 450-466.
  40. Xacur, Oscar Alberto Quijano & Garrido, José, 2018. "Bayesian credibility for GLMs," Insurance: Mathematics and Economics, Elsevier, vol. 83(C), pages 180-189.
  41. Martin Branda, 2014. "Optimization Approaches to Multiplicative Tariff of Rates Estimation in Non-Life Insurance," Asia-Pacific Journal of Operational Research (APJOR), World Scientific Publishing Co. Pte. Ltd., vol. 31(05), pages 1-17.
  42. Kudryavtsev, Andrey A., 2009. "Using quantile regression for rate-making," Insurance: Mathematics and Economics, Elsevier, vol. 45(2), pages 296-304, October.
  43. Shengkun Xie & Rebecca Luo, 2022. "Measuring Variable Importance in Generalized Linear Models for Modeling Size of Loss Distributions," Mathematics, MDPI, vol. 10(10), pages 1-19, May.
  44. Mihaela COVRIG & Dumitru BADEA, 2017. "Some Generalized Linear Models for the Estimation of the Mean Frequency of Claims in Motor Insurance," ECONOMIC COMPUTATION AND ECONOMIC CYBERNETICS STUDIES AND RESEARCH, Faculty of Economic Cybernetics, Statistics and Informatics, vol. 51(4), pages 91-107.
  45. Jeonghwan Kim & Woojoo Lee, 2019. "On testing the hidden heterogeneity in negative binomial regression models," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 82(4), pages 457-470, May.
  46. Pinho, Luis Gustavo B. & Nobre, Juvêncio S. & Singer, Julio M., 2015. "Cook’s distance for generalized linear mixed models," Computational Statistics & Data Analysis, Elsevier, vol. 82(C), pages 126-136.
  47. 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.
  48. Yuqing Zhang & Neil Walton, 2019. "Adaptive Pricing in Insurance: Generalized Linear Models and Gaussian Process Regression Approaches," Papers 1907.05381, arXiv.org.
  49. Tzougas, George & Karlis, Dimitris, 2020. "An EM algorithm for fitting a new class of mixed exponential regression models with varying dispersion," LSE Research Online Documents on Economics 104027, London School of Economics and Political Science, LSE Library.
  50. Oscar Alberto Quijano Xacur, 2019. "The unifed distribution," Journal of Statistical Distributions and Applications, Springer, vol. 6(1), pages 1-12, December.
  51. Sarabia, José María & Gómez-Déniz, Emilio & Prieto, Faustino & Jordá, Vanesa, 2016. "Risk aggregation in multivariate dependent Pareto distributions," Insurance: Mathematics and Economics, Elsevier, vol. 71(C), pages 154-163.
  52. Bortoluzzo, Adriana B. & Claro, Danny P. & Caetano, Marco Antonio L. & Artes, Rinaldo, 2009. "Estimating Claim Size and Probability in the Auto-insurance Industry: the Zero-adjusted Inverse Gaussian (ZAIG) Distribution," Insper Working Papers wpe_175, Insper Working Paper, Insper Instituto de Ensino e Pesquisa.
  53. Inmaculada Peña-Sanchez, 2019. "Applying the Tweedie model for improved microinsurance pricing," The Geneva Papers on Risk and Insurance - Issues and Practice, Palgrave Macmillan;The Geneva Association, vol. 44(3), pages 365-381, July.
  54. Christoph Rheinberger & Hans E. Romang & Michael Bründl, 2013. "Proportional loss functions for debris flow events," Post-Print hal-02643847, HAL.
  55. Claro, Danny P., 2009. "Estimating claim size and probability in the auto-insurance industry: the zeroadjusted Inverse Gaussian (ZAIG) distribution," Insper Working Papers wpe_159, Insper Working Paper, Insper Instituto de Ensino e Pesquisa.
  56. Lee, Woojoo & Kim, Jeonghwan & Ahn, Jae Youn, 2020. "The Poisson random effect model for experience ratemaking: Limitations and alternative solutions," Insurance: Mathematics and Economics, Elsevier, vol. 91(C), pages 26-36.
  57. Bufalo, Michele & Ceci, Claudia & Orlando, Giuseppe, 2024. "Addressing the financial impact of natural disasters in the era of climate change," The North American Journal of Economics and Finance, Elsevier, vol. 73(C).
  58. 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.
  59. William Guevara-Alarc'on & Luz Mery Gonz'alez & Armando Antonio Zarruk, 2017. "The partial damage loss cover ratemaking of the automobile insurance using generalized linear models," Papers 1707.03391, arXiv.org.
  60. Liangjun Su & Martin Spindler, 2013. "Nonparametric Testing for Asymmetric Information," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 31(2), pages 208-225, April.
  61. Mihaela Covrig & Iulian Mircea & Gheorghita Zbaganu & Alexandru Coser & Alexandru Tindeche, 2015. "Using R In Generalized Linear Models," Romanian Statistical Review, Romanian Statistical Review, vol. 63(3), pages 33-45, September.
  62. 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.
  63. Chung, Jae Young & Sun, Mi Suk & Kim, Hyun Ju, 2018. "What makes bullies and victims in Korean elementary schools?," Children and Youth Services Review, Elsevier, vol. 94(C), pages 132-139.
  64. Tsyganov, Aleksander & Baskakov, Valery & Yazykov, Andrey & Sheparnev, Nikolay & Yanenko, Evgeny & Grysenkova, Yulia, 2019. "The impact of the bonus-malus system on the insurance ratemaking in the system of compulsory insurance of the responsibility of transport owners in Russia," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 56, pages 123-141.
  65. Alex Jose & Angus S. Macdonald & George Tzougas & George Streftaris, 2022. "A Combined Neural Network Approach for the Prediction of Admission Rates Related to Respiratory Diseases," Risks, MDPI, vol. 10(11), pages 1-35, November.
  66. Avanzi, Benjamin & Wong, Bernard & Yang, Xinda, 2016. "A micro-level claim count model with overdispersion and reporting delays," Insurance: Mathematics and Economics, Elsevier, vol. 71(C), pages 1-14.
  67. Tingting Chen & Anthony Francis Desmond & Peter Adamic, 2023. "Generalized Additive Modelling of Dependent Frequency and Severity Distributions for Aggregate Claims," Journal of Statistical and Econometric Methods, SCIENPRESS Ltd, vol. 12(4), pages 1-1.
  68. Emilio Gómez-Déniz & Enrique Calderín-Ojeda, 2020. "A Survey of the Individual Claim Size and Other Risk Factors Using Credibility Bonus-Malus Premiums," Risks, MDPI, vol. 8(1), pages 1-19, February.
  69. Tzougas, George, 2020. "EM estimation for the Poisson-Inverse Gamma regression model with varying dispersion: an application to insurance ratemaking," LSE Research Online Documents on Economics 106539, London School of Economics and Political Science, LSE Library.
  70. 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.
  71. 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.
  72. Sarah R. Al-Dawsari & Khalaf S. Sultan, 2021. "Inverted Weibull Regression Models and Their Applications," Stats, MDPI, vol. 4(2), pages 1-22, April.
  73. Adriana Dima & Elena Radu & Ecaterina Milica Dobrota & Adrian Otoiu & Alina Florentina Saracu, 2023. "Sustainable Development of E-commerce in the Post-COVID Times: A Mixed-Methods Analysis of Pestle Factors," The AMFITEATRU ECONOMIC journal, Academy of Economic Studies - Bucharest, Romania, vol. 25(S17), pages 1095-1095, November.
  74. Ana Preda & Mirela Monea & Lorand Bogdanffy, 2016. "Simulation Insured Results by Purchasing a Life Insurance," Annals of the University of Petrosani, Economics, University of Petrosani, Romania, vol. 16(2), pages 109-116.
  75. Huang, Yifan & Meng, Shengwang, 2020. "A Bayesian nonparametric model and its application in insurance loss prediction," Insurance: Mathematics and Economics, Elsevier, vol. 93(C), pages 84-94.
  76. Gao, Suhao & Yu, Zhen, 2023. "Parametric expectile regression and its application for premium calculation," Insurance: Mathematics and Economics, Elsevier, vol. 111(C), pages 242-256.
  77. Riccardo Borgoni & Andrea Gilardi & Diego Zappa, 2021. "Assessing the Risk of Car Crashes in Road Networks," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 156(2), pages 429-447, August.
  78. Simon CK Lee, 2020. "Delta Boosting Implementation of Negative Binomial Regression in Actuarial Pricing," Risks, MDPI, vol. 8(1), pages 1-21, February.
  79. Liang Yang & Zhengxiao Li & Shengwang Meng, 2020. "Risk Loadings in Classification Ratemaking," Papers 2002.01798, arXiv.org, revised Jan 2022.
  80. 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.
  81. Qimeng Pan & Lysa Porth & Hong Li, 2022. "Assessing the Effectiveness of the Actuaries Climate Index for Estimating the Impact of Extreme Weather on Crop Yield and Insurance Applications," Sustainability, MDPI, vol. 14(11), pages 1-24, June.
  82. Sungjin Ahn & Taehui Kim & Ji-Myong Kim, 2020. "Sustainable Risk Assessment through the Analysis of Financial Losses from Third-Party Damage in Bridge Construction," Sustainability, MDPI, vol. 12(8), pages 1-15, April.
  83. Jiří Valecký, . "Calculation of Solvency Capital Requirements for Non-life Underwriting Risk Using Generalized Linear Models," Prague Economic Papers, University of Economics, Prague, vol. 0, pages 1-17.
  84. Tan, Chong It, 2016. "Varying transition rules in bonus–malus systems: From rules specification to determination of optimal relativities," Insurance: Mathematics and Economics, Elsevier, vol. 68(C), pages 134-140.
  85. Kang, Seul Ki & Peng, Liang & Xiao, Hongmin, 2020. "Risk analysis with categorical explanatory variables," Insurance: Mathematics and Economics, Elsevier, vol. 91(C), pages 238-243.
  86. Shushi, Tomer & Yao, Jing, 2020. "Multivariate risk measures based on conditional expectation and systemic risk for Exponential Dispersion Models," Insurance: Mathematics and Economics, Elsevier, vol. 93(C), pages 178-186.
  87. Fridgen, Gilbert & Kräussl, Roman & Papageorgiou, Orestis & Tugnetti, Alessandro, 2023. "The fundamental value of art NFTs," CFS Working Paper Series 709, Center for Financial Studies (CFS).
  88. 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.
IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.