Pair Copula Constructions for Insurance Experience Rating

DOI10.1080/01621459.2017.1330692zbMath1398.62323OpenAlexW2661019854MaRDI QIDQ4690933

Peng Shi, Lu Yang

Publication date: 23 October 2018

Published in: Journal of the American Statistical Association (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/01621459.2017.1330692

zbMATH Keywords

predictive distributionmixture regressionzero inflationgovernment insurancemixed D-vine

Mathematics Subject Classification ID

Related Items (21)

Copula Regression for Compound Distributions with Endogenous Covariates with Applications in Insurance Deductible Pricing ⋮ MULTI-STATE MODELLING OF CUSTOMER CHURN ⋮ A new class of copula regression models for modelling multivariate heavy-tailed data ⋮ A two-stage model for high-risk prediction in insurance ratemaking: asymptotics and inference ⋮ Predictive risk analysis using a collective risk model: choosing between past frequency and aggregate severity information ⋮ Analysis of ordinal and continuous longitudinal responses using pair copula construction ⋮ Knowledge Learning of Insurance Risks Using Dependence Models ⋮ Regression for copula-linked compound distributions with applications in modeling aggregate insurance claims ⋮ Bayesian variable selection for non‐Gaussian responses: a marginally calibrated copula approach ⋮ Non-Life Insurance Risk Classification Using Categorical Embedding ⋮ A simple Bayesian state-space approach to the collective risk models ⋮ Enhanced pricing and management of bundled insurance risks with dependence-aware prediction using pair copula construction ⋮ A multivariate frequency-severity framework for healthcare data breaches ⋮ Bivariate distribution regression with application to insurance data ⋮ Diagnostic tests before modeling longitudinal actuarial data ⋮ Parametric expectile regression and its application for premium calculation ⋮ Bayesian credibility under a bivariate prior on the frequency and the severity of claims ⋮ A multi-year microlevel collective risk model ⋮ Predictive analytics of insurance claims using multivariate decision trees ⋮ Variational Bayes Estimation of Discrete-Margined Copula Models With Application to Time Series ⋮ Satisficing credibility for heterogeneous risks

Uses Software

• SemiPar

Cites Work

• Pair-copula constructions of multiple dependence
• Selecting and estimating regular vine copulae and application to financial returns
• Sequential Bayesian model selection of regular vine copulas
• Multilevel modeling of insurance claims using copulas
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• On the simplified pair-copula construction -- simply useful or too simplistic?
• Heavy-tailed longitudinal data modeling using copulas
• A longitudinal data analysis interpretation of credibility models
• A generalization of the beta distribution with applications
• Model selection for discrete regular vine copulas
• Comorbidity of chronic diseases in the elderly: patterns identified by a copula design for mixed responses
• Vines -- a new graphical model for dependent random variables.
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• Multivariate longitudinal modeling of insurance company expenses
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• Dependence Modeling with Copulas
• Some Generalized Functions for the Size Distribution of Income
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• Uncertainty Analysis with High Dimensional Dependence Modelling
• A Two-Part Random-Effects Model for Semicontinuous Longitudinal Data
• Semiparametric Regression
• Pair Copula Constructions for Multivariate Discrete Data
• Modeling Longitudinal Data Using a Pair-Copula Decomposition of Serial Dependence
• Hierarchical Insurance Claims Modeling
• A Primer on Copulas for Count Data
• Credibility Using Copulas

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