On modeling left-truncated loss data using mixtures of distributions

Martin Blostein and Tatjana Miljkovic

Insurance: Mathematics and Economics, 2019, vol. 85, issue C, 35-46

Abstract: A new statistical methodology is developed for fitting left-truncated loss data by using the G-component finite mixture model with any combination of Gamma, Lognormal, and Weibull distributions. The EM algorithm, along with the emEM initialization strategy, is employed for model fitting. We propose a new grid map which considers the model selection criterion (AIC or BIC) and risk measures at the same time, by using the entire space of models under consideration. A simulation study validates our proposed approach. The application of the proposed methodology and use of new grid maps are illustrated through analyzing a real data set that includes left-truncated insurance losses.

Keywords: Finite mixture models; EM algorithm; Loss modeling; Left-truncation; Grid map (search for similar items in EconPapers)
JEL-codes: C02 C40 C60 (search for similar items in EconPapers)
Date: 2019
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Citations: View citations in EconPapers (8)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:insuma:v:85:y:2019:i:c:p:35-46

DOI: 10.1016/j.insmatheco.2018.12.001

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