A CLASS OF MIXTURE OF EXPERTS MODELS FOR GENERAL INSURANCE: APPLICATION TO CORRELATED CLAIM FREQUENCIES

DOI10.1017/asb.2019.25zbMath1427.91227OpenAlexW2971556193WikidataQ127297644 ScholiaQ127297644MaRDI QIDQ4972120

Andrei L. Badescu, T. C. Fung, X. Sheldon Lin

Publication date: 22 November 2019

Published in: ASTIN Bulletin (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1017/asb.2019.25

zbMATH Keywords

mixture of experts modelsErlang count modelsexpectation conditional maximization algorithmlogit-weighted gating functionsmultivariate count regression

Mathematics Subject Classification ID

Applications of statistics to actuarial sciences and financial mathematics (62P05) Actuarial mathematics (91G05)

Related Items (12)

JOINT MODELING OF CLAIM FREQUENCIES AND BEHAVIORAL SIGNALS IN MOTOR INSURANCE ⋮ Gamma mixture density networks and their application to modelling insurance claim amounts ⋮ The multivariate mixed negative binomial regression model with an application to insurance a posteriori ratemaking ⋮ Bayesian Multivariate Mixed Poisson Models with Copula-Based Mixture ⋮ Bivariate Mixed Poisson Regression Models with Varying Dispersion ⋮ Mixture Composite Regression Models with Multi-type Feature Selection ⋮ Multivariate mixed Poisson generalized inverse Gaussian INAR(1) regression ⋮ Modeling frequency and severity of claims with the zero-inflated generalized cluster-weighted models ⋮ A New Class of Severity Regression Models with an Application to IBNR Prediction ⋮ A class of mixture of experts models for general insurance: theoretical developments ⋮ Two-step risk analysis in insurance ratemaking ⋮ Fitting Censored and Truncated Regression Data Using the Mixture of Experts Models

Uses Software

• EMpht

Cites Work

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