Dirichlet process mixture models for insurance loss data

DOI10.1080/03461238.2017.1402086zbMath1416.91188OpenAlexW2732897285MaRDI QIDQ4583621

Ryan Martin, Liang Hong

Publication date: 31 August 2018

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

Full work available at URL: https://doi.org/10.1080/03461238.2017.1402086

zbMATH Keywords

model misspecificationnonparametric Bayesgeneral insuranceproperty and casualty insuranceDanish fire losses dataNorwegian fire losses dataUS allocated loss adjustment expenses data

Mathematics Subject Classification ID

Related Items (5)

Conformal Prediction Credibility Intervals ⋮ Model misspecification, Bayesian versus credibility estimation, and Gibbs posteriors ⋮ Gibbs posterior inference on value-at-risk ⋮ Valid Model-Free Prediction of Future Insurance Claims ⋮ Sample Size Determination for Credibility Estimation

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