Extending composite loss models using a general framework of advanced computational tools

DOI10.1080/03461238.2019.1596151zbMath1422.91351OpenAlexW2933978029MaRDI QIDQ5193489

Tatjana Miljkovic, Bettina Grün

Publication date: 10 September 2019

Published in: Scandinavian Actuarial Journal (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/03461238.2019.1596151

zbMATH Keywords

goodness-of-fitrisk measuresheavy tailed distributionscomposite modelsDanish fire insurance data

Mathematics Subject Classification ID

Related Items (20)

A new class of copula regression models for modelling multivariate heavy-tailed data ⋮ Estimation of lifetime parameters of the modified extended exponential distribution with application to a mechanical model ⋮ Analyzing insurance data with an exponentiated composite inverse Gamma-Pareto model ⋮ Finite-sample performance of the T- and W-estimators for the Pareto tail index under data truncation and censoring ⋮ PHASE-TYPE DISTRIBUTIONS FOR CLAIM SEVERITY REGRESSION MODELING ⋮ Sequential Monte Carlo samplers to fit and compare insurance loss models ⋮ Mixture Composite Regression Models with Multi-type Feature Selection ⋮ Maximum weighted likelihood estimator for robust heavy-tail modelling of finite mixture models ⋮ Soft splicing model: bridging the gap between composite model and finite mixture model ⋮ Deep quantile and deep composite triplet regression ⋮ The Automated Bias-Corrected and Accelerated Bootstrap Confidence Intervals for Risk Measures ⋮ Phase-type mixture-of-experts regression for loss severities ⋮ Composite models with underlying folded distributions ⋮ ROBUST ESTIMATION OF LOSS MODELS FOR LOGNORMAL INSURANCE PAYMENT SEVERITY DATA ⋮ GENERALIZING THE LOG-MOYAL DISTRIBUTION AND REGRESSION MODELS FOR HEAVY-TAILED LOSS DATA ⋮ A New Class of Severity Regression Models with an Application to IBNR Prediction ⋮ Analysis of skewed data by using compound Poisson exponential distribution with applications to insurance claims ⋮ Univariate and bivariate compound models based on random sum of variates with application to the insurance losses data ⋮ Assessing the performance of confidence intervals for high quantiles of Burr XII and Inverse Burr mixtures ⋮ Using Model Averaging to Determine Suitable Risk Measure Estimates

Uses Software

• R
• numDeriv
• pracma
• SMPracticals

Cites Work

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• Modeling claims data with composite Stoppa models
• New composite models for the Danish fire insurance data
• An evaluation of the reconstructed coefficient of determination and potential adjustments
• From grouped to de-grouped data: a new approach in distribution fitting for grouped data
• Modeling veterans’ health benefit grants using the expectation maximization algorithm
• Modeling with Weibull-Pareto Models
• Modeling Severity and Measuring Tail Risk of Norwegian Fire Claims
• Modeling actuarial data with a composite lognormal-Pareto model
• On composite lognormal-Pareto models
• A new look at the statistical model identification

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