GENERALIZING THE LOG-MOYAL DISTRIBUTION AND REGRESSION MODELS FOR HEAVY-TAILED LOSS DATA

DOI10.1017/asb.2020.35zbMath1472.91039arXiv1912.09560OpenAlexW3095373709MaRDI QIDQ5157764

Zheng-xiao Li, Shengwang Meng, Jan Beirlant

Publication date: 20 October 2021

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

Full work available at URL: https://arxiv.org/abs/1912.09560

zbMATH Keywords

Chinese earthquake lossesfire claim data setgeneralized log-Moyal distributionNorwegian fire lossesparametric regression modeling

Mathematics Subject Classification ID

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

Related Items (2)

A new class of copula regression models for modelling multivariate heavy-tailed data ⋮ A new distributional approach: estimation, Monte Carlo simulation and applications to the biomedical data sets

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Bayesian approaches for analyzing earthquake catastrophic risk
• Regression models for positive random variables
• A generalized beta copula with applications in modeling multivariate long-tailed data
• Burr regression and portfolio segmentation
• Compound unimodal distributions for insurance losses
• Modelling censored losses using splicing: a global fit strategy with mixed Erlang and extreme value distributions
• On generalized log-Moyal distribution: a new heavy tailed size distribution
• Modelling losses using an exponential-inverse Gaussian distribution
• Modeling loss data using composite models
• Tail conditional moments for elliptical and log-elliptical distributions
• Skew mixture models for loss distributions: a Bayesian approach
• Bayesian analysis of loss reserving using dynamic models with generalized beta distribution
• Modeling loss data using mixtures of distributions
• Folded and log-folded-tdistributions as models for insurance loss data
• The Double Pareto-Lognormal Distribution—A New Parametric Model for Size Distributions
• Plotting with confidence: Graphical comparisons of two populations
• MODELLING INSURANCE LOSSES USING CONTAMINATED GENERALISED BETA TYPE-II DISTRIBUTION
• FITTING MIXTURES OF ERLANGS TO CENSORED AND TRUNCATED DATA USING THE EM ALGORITHM
• THE FULL TAILS GAMMA DISTRIBUTION APPLIED TO MODEL EXTREME VALUES
• Modeling claims data with composite Stoppa models
• Reinsurance
• Statistics of Extremes
• Gamma-Generalized Inverse Gaussian Class of Distributions with Applications
• Modeling with Weibull-Pareto Models
• Extending composite loss models using a general framework of advanced computational tools
• The exponentiated Fréchet regression: an alternative model for actuarial modelling purposes
• Generalized Inverse Gamma Distribution and its Application in Reliability
• Hierarchical Insurance Claims Modeling
• Modeling actuarial data with a composite lognormal-Pareto model
• On composite lognormal-Pareto models
• A Generalization of the Gamma Distribution

This page was built for publication: GENERALIZING THE LOG-MOYAL DISTRIBUTION AND REGRESSION MODELS FOR HEAVY-TAILED LOSS DATA