A default Bayesian approach for regression on extremes

DOI10.1177/1471082X1001100606zbMath1420.62108OpenAlexW2097954730MaRDI QIDQ5193324

Stefano Cabras, Dani Gamerman, María Eugenia Castellanos

Publication date: 10 September 2019

Published in: Statistical Modelling (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1177/1471082x1001100606

zbMATH Keywords

extreme valuesJeffreys' prior\(K\)-year return levelnon-homogenous Poisson-GPDpeaks over the threshold

Mathematics Subject Classification ID

Bayesian inference (62F15) Stationary stochastic processes (60G10) Statistics of extreme values; tail inference (62G32)

Related Items (6)

Bayesian inference for extreme quantiles of heavy tailed distributions ⋮ Bayesian approaches for analyzing earthquake catastrophic risk ⋮ Regression models for exceedance data: a new approach ⋮ Regression models for time-varying extremes ⋮ Dynamic linear seasonal models applied to extreme temperature data: a Bayesian approach using the r-larger order statistics distribution ⋮ Regression models to dependence for exceedance

Uses Software

• ismev

Cites Work

• A default Bayesian procedure for the generalized Pareto distribution
• Statistical inference using extreme order statistics
• On spatial extremes: with application to a rainfall problem
• Sur la distribution limite du terme maximum d'une série aléatoire
• Bayesian analysis of extreme events with threshold estimation
• Bayesian Spatial Modeling of Extreme Precipitation Return Levels
• Bayesian Measures of Model Complexity and Fit
• Extreme value analysis within a parametric outlier detection framework
• Generalized Additive Modelling of Sample Extremes
• An introduction to statistical modeling of extreme values
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