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Modeling loss data using composite models

Citations

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Cited by:

  1. Fung, Tsz Chai, 2022. "Maximum weighted likelihood estimator for robust heavy-tail modelling of finite mixture models," Insurance: Mathematics and Economics, Elsevier, vol. 107(C), pages 180-198.
  2. Nada M Alfaer & Sarah A Bandar & Omid Kharazmi & Hazem Al-Mofleh & Zubair Ahmad & Ahmed Z Afify, 2023. "Classical and Bayesian estimation for type-I extended-F family with an actuarial application," PLOS ONE, Public Library of Science, vol. 18(2), pages 1-23, February.
  3. Shi, Yue & Punzo, Antonio & Otneim, Håkon & Maruotti, Antonello, 2025. "Hidden semi-Markov models for rainfall-related insurance claims," Insurance: Mathematics and Economics, Elsevier, vol. 120(C), pages 91-106.
  4. Reynkens, Tom & Verbelen, Roel & Beirlant, Jan & Antonio, Katrien, 2017. "Modelling censored losses using splicing: A global fit strategy with mixed Erlang and extreme value distributions," Insurance: Mathematics and Economics, Elsevier, vol. 77(C), pages 65-77.
  5. Ruben Dewitte & Michel Dumont & Glenn Rayp & Peter Willemé, 2022. "Unobserved heterogeneity in the productivity distribution and gains from trade," Canadian Journal of Economics/Revue canadienne d'économique, John Wiley & Sons, vol. 55(3), pages 1566-1597, August.
  6. Min Deng & Mostafa S. Aminzadeh, 2023. "Bayesian Inference for the Loss Models via Mixture Priors," Risks, MDPI, vol. 11(9), pages 1-27, August.
  7. Muhammad Hilmi Abdul Majid & Kamarulzaman Ibrahim & Nurulkamal Masseran, 2023. "Three-Part Composite Pareto Modelling for Income Distribution in Malaysia," Mathematics, MDPI, vol. 11(13), pages 1-15, June.
  8. Chen, Zezhun & Dassios, Angelos & Tzougas, George, 2022. "EM estimation for the bivariate mixed exponential regression model," LSE Research Online Documents on Economics 115132, London School of Economics and Political Science, LSE Library.
  9. Jackie Li & Jia Liu, 2023. "Claims Modelling with Three-Component Composite Models," Risks, MDPI, vol. 11(11), pages 1-16, November.
  10. Bae, Taehan & Miljkovic, Tatjana, 2024. "Loss modeling with the size-biased lognormal mixture and the entropy regularized EM algorithm," Insurance: Mathematics and Economics, Elsevier, vol. 117(C), pages 182-195.
  11. Walena Anesu Marambakuyana & Sandile Charles Shongwe, 2024. "Composite and Mixture Distributions for Heavy-Tailed Data—An Application to Insurance Claims," Mathematics, MDPI, vol. 12(2), pages 1-23, January.
  12. Shi, Yue & Punzo, Antonio & Otneim, Håkon & Maruotti, Antonello, 2023. "Hidden semi-Markov models for rainfall-related insurance claims," Discussion Papers 2023/17, Norwegian School of Economics, Department of Business and Management Science.
  13. 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.
  14. Enrique Calderín-Ojeda, 2018. "A Note on Parameter Estimation in the Composite Weibull–Pareto Distribution," Risks, MDPI, vol. 6(1), pages 1-8, February.
  15. Salvatore D. Tomarchio & Luca Bagnato & Antonio Punzo, 2024. "Model-based clustering using a new multivariate skew distribution," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 18(1), pages 61-83, March.
  16. Ahmed Z. Afify & Ahmed M. Gemeay & Noor Akma Ibrahim, 2020. "The Heavy-Tailed Exponential Distribution: Risk Measures, Estimation, and Application to Actuarial Data," Mathematics, MDPI, vol. 8(8), pages 1-28, August.
  17. Semhar Michael & Tatjana Miljkovic & Volodymyr Melnykov, 2020. "Mixture modeling of data with multiple partial right-censoring levels," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 14(2), pages 355-378, June.
  18. Zezhun Chen & Angelos Dassios & George Tzougas, 2022. "EM Estimation for the Bivariate Mixed Exponential Regression Model," Risks, MDPI, vol. 10(5), pages 1-13, May.
  19. Wilson Gyasi & Kahadawala Cooray, 2024. "New generalized extreme value distribution with applications to extreme temperature data," Environmetrics, John Wiley & Sons, Ltd., vol. 35(3), May.
  20. Blostein, Martin & Miljkovic, Tatjana, 2019. "On modeling left-truncated loss data using mixtures of distributions," Insurance: Mathematics and Economics, Elsevier, vol. 85(C), pages 35-46.
  21. Marco Bee, 2024. "On discriminating between lognormal and Pareto tail: an unsupervised mixture-based approach," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 18(2), pages 251-269, June.
  22. Bhati, Deepesh & Ravi, Sreenivasan, 2018. "On generalized log-Moyal distribution: A new heavy tailed size distribution," Insurance: Mathematics and Economics, Elsevier, vol. 79(C), pages 247-259.
  23. Patrick Osatohanmwen, 2025. "A new two-component hybrid model for highly right-skewed data: estimation algorithm and application to finance and rainfall data," BEMPS - Bozen Economics & Management Paper Series BEMPS108, Faculty of Economics and Management at the Free University of Bozen.
  24. Li, Zhengxiao & Wang, Fei & Zhao, Zhengtang, 2024. "A new class of composite GBII regression models with varying threshold for modeling heavy-tailed data," Insurance: Mathematics and Economics, Elsevier, vol. 117(C), pages 45-66.
  25. Punzo, Antonio & Bagnato, Luca & Maruotti, Antonello, 2018. "Compound unimodal distributions for insurance losses," Insurance: Mathematics and Economics, Elsevier, vol. 81(C), pages 95-107.
  26. Girish Aradhye & George Tzougas & Deepesh Bhati, 2024. "A Copula-Based Bivariate Composite Model for Modelling Claim Costs," Mathematics, MDPI, vol. 12(2), pages 1-17, January.
  27. Wei Zhao & Saima K Khosa & Zubair Ahmad & Muhammad Aslam & Ahmed Z Afify, 2020. "Type-I heavy tailed family with applications in medicine, engineering and insurance," PLOS ONE, Public Library of Science, vol. 15(8), pages 1-24, August.
  28. Min Deng & Mostafa Aminzadeh & Min Ji, 2021. "Bayesian Predictive Analysis of Natural Disaster Losses," Risks, MDPI, vol. 9(1), pages 1-23, January.
  29. Mahsa Salajegheh & Mehdi Jabbari Nooghabi & Kheirolah Okhli, 2025. "A Bayesian approach for modeling heavy tailed insurance claim data based on the contaminated lognormal distribution," METRON, Springer;Sapienza Università di Roma, vol. 83(2), pages 213-234, August.
  30. Patrick Osatohanmwen, 2025. "A New Two-Component Hybrid Model for Highly Right-Skewed Data: Estimation Algorithm and Application to Rainfall Data from South Tyrol, Italy," Mathematics, MDPI, vol. 13(18), pages 1-19, September.
  31. Zoia, Maria Grazia & Biffi, Paola & Nicolussi, Federica, 2018. "Value at risk and expected shortfall based on Gram-Charlier-like expansions," Journal of Banking & Finance, Elsevier, vol. 93(C), pages 92-104.
  32. Miljkovic, Tatjana & Grün, Bettina, 2016. "Modeling loss data using mixtures of distributions," Insurance: Mathematics and Economics, Elsevier, vol. 70(C), pages 387-396.
  33. Johan René van Dorp & Ekundayo Shittu, 2024. "Two-sided distributions with applications in insurance loss modeling," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 33(3), pages 827-861, July.
  34. Naderi, Mehrdad & Hashemi, Farzane & Bekker, Andriette & Jamalizadeh, Ahad, 2020. "Modeling right-skewed financial data streams: A likelihood inference based on the generalized Birnbaum–Saunders mixture model," Applied Mathematics and Computation, Elsevier, vol. 376(C).
  35. Johan René Dorp & Ekundayo Shittu, 2025. "Modeling heavy-tails with two-piece Burr distributions via conditional values-at-risk," METRON, Springer;Sapienza Università di Roma, vol. 83(2), pages 151-182, August.
  36. Bowen Liu & Malwane M. A. Ananda, 2022. "A Generalized Family of Exponentiated Composite Distributions," Mathematics, MDPI, vol. 10(11), pages 1-18, June.
  37. Dewitte, Ruben, 2020. "From Heavy-Tailed Micro to Macro: on the characterization of firm-level heterogeneity and its aggregation properties," MPRA Paper 103170, University Library of Munich, Germany.
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