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ArticleModeling loss data using mixtures of distributions

Tatjana Miljkovic2016

Article2016

Modeling loss data using mixtures of distributions

Tatjana Miljkovic · Bettina Grün

101 citations·0/0 files stored·Insurance Mathematics and Economics

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Probability and Risk Models Statistical Distribution Estimation and Applications Bayesian Methods and Mixture Models

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References

1999Loss Models: From Data to Decisions 1997Estimating the Tails of Loss Severity Distributions Using Extreme Value Theory 1988Concomitant-Variable Latent-Class Models 2005Modeling actuarial data with a composite lognormal-Pareto model 2007On composite lognormal-Pareto models 1997Discussion of the Danish Data on Large Fire Insurance Losses 2010Modeling and Evaluating Insurance Losses Via Mixtures of Erlang Distributions 2014Modeling loss data using composite models

Cited by

2017Data breaches: Goodness of fit, pricing, and risk measurement 2018On generalized log-Moyal distribution: A new heavy tailed size distribution 2017Modelling censored losses using splicing: A global fit strategy with mixed Erlang and extreme value distributions 2019Extending composite loss models using a general framework of advanced computational tools 2021Recent Challenges in Actuarial Science

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2017Modelling censored losses using splicing: A global fit strategy with mixed Erlang and extreme value distributionsarticle · 7 shared references 2018On generalized log-Moyal distribution: A new heavy tailed size distributionarticle · 6 shared references 2019Extending composite loss models using a general framework of advanced computational toolsarticle · 6 shared references 2012Modeling with Weibull-Pareto Modelsarticle · 5 shared references 2010Composite Lognormal–Pareto model with random thresholdarticle · 5 shared references 2017Compound unimodal distributions for insurance lossesarticle · 5 shared references

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Year2016

Typearticle

Published2016-07-17

VenueInsurance Mathematics and Economics

ISSN-L0167-6687

Languageen

Citations101

Files0 public / 0

ShelfProbability and Risk Models

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doi10.1016/j.insmatheco.2016.06.019

openalex_workW2495882236

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