The Poisson random effect model for experience ratemaking: limitations and alternative solutions
From MaRDI portal
Publication:2306087
DOI10.1016/j.insmatheco.2019.12.004zbMath1435.91157arXiv1811.04522OpenAlexW2996772850WikidataQ126429273 ScholiaQ126429273MaRDI QIDQ2306087
Jae Youn Ahn, Jeonghwan Kim, Woo-Joo Lee
Publication date: 20 March 2020
Published in: Insurance Mathematics \& Economics (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/1811.04522
negative binomial distributiondependenceclaim frequencyexperience ratemakingPoisson random effect model
Related Items (1)
Uses Software
Cites Work
- Misspecifying the shape of a random effects distribution: why getting it wrong may not matter
- Credibility premiums for the zero-inflated Poisson model and new hunger for bonus interpretation
- Statistical concepts of \textit{a priori} and \textit{a posteriori} risk classification in insurance
- On modeling claim frequency data in general insurance with extra zeros
- Models for discrete longitudinal data.
- Misspecified maximum likelihood estimates and generalised linear mixed models
- Actuarial Modelling of Claim Counts
- Fixed versus Random Effects in Poisson Regression Models for Claim Counts: A Case Study with Motor Insurance
- Designing Optimal Bonus-Malus Systems from Different Types of Claims
- Testing for Neglected Heterogeneity
- A locally most powerful test for homogeneity with many strata
- Negative binomial and mixed poisson regression
- Testing Approaches for Overdispersion in Poisson Regression versus the Generalized Poisson Model
- Regression Modeling with Actuarial and Financial Applications
- A POSTERIORI RATEMAKING WITH PANEL DATA
- Bayesian Gaussian Copula Factor Models for Mixed Data
- Generalized Linear Models for Insurance Data
- Negative binomial loglinear mixed models
This page was built for publication: The Poisson random effect model for experience ratemaking: limitations and alternative solutions
