Bayesian inference for extreme quantiles of heavy tailed distributions

DOI10.1016/j.spl.2016.02.020zbMath1384.62086OpenAlexW2296482986MaRDI QIDQ274181

Rafael B. A. Farias, Michel H. Montoril, José A. A. Andrade

Publication date: 22 April 2016

Published in: Statistics \& Probability Letters (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.spl.2016.02.020

zbMATH Keywords

heavy tailhigh quantileHPD interval

Mathematics Subject Classification ID

Asymptotic distribution theory in statistics (62E20) Bayesian inference (62F15)

Related Items (2)

Gamma mixture of generalized error distribution ⋮ The beta skew \(t\) distribution and its properties

Uses Software

• R
• CODA

Cites Work

• Confidence regions for high quantiles of a heavy tailed distribution
• Weak convergence and optimal scaling of random walk Metropolis algorithms
• Empirical-likelihood-based confidence interval for the mean with a heavy-tailed distribution.
• A new class of models for heavy tailed distributions in finance and insurance risk
• Skew mixture models for loss distributions: a Bayesian approach
• Bayesian analysis of extreme events with threshold estimation
• Statistics of Extremes
• Bayesian Methods in Extreme Value Modelling: A Review and New Developments
• A default Bayesian approach for regression on extremes
• Modeling actuarial data with a composite lognormal-Pareto model

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