Anticipating Catastrophes through Extreme Value Modelling

DOI10.1111/1467-9876.00413zbMath1111.62366OpenAlexW1978662910WikidataQ63362838 ScholiaQ63362838MaRDI QIDQ3435776

Luís Raúl Pericchi, Stuart G. Coles

Publication date: 7 May 2007

Published in: Journal of the Royal Statistical Society Series C: Applied Statistics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1111/1467-9876.00413

Mathematics Subject Classification ID

Applications of statistics to environmental and related topics (62P12) Statistics of extreme values; tail inference (62G32)

Related Items (22)

Bayesian comparison of different rainfall depth-duration-frequency relationships ⋮ Consistency of Bayesian inference for multivariate max-stable distributions ⋮ Full Bayesian Analysis for a Class of Jump-Diffusion Models ⋮ Improved inference on risk measures for univariate extremes ⋮ Permutation bootstrap and the block maxima method ⋮ OR/MS research in disaster operations management ⋮ A semi-parametric Bayesian extreme value model using a Dirichlet process mixture of gamma densities ⋮ An emergency logistics distribution routing model for unexpected events ⋮ Practical issues with modeling extreme Brazilian rainfall ⋮ Accounting for the threshold uncertainity in extreme value estimation ⋮ Assessing conditional extremal risk of flooding in Puerto Rico ⋮ Timeliness evaluation of emergency resource scheduling ⋮ Modeling Waves of Extreme Temperature: The Changing Tails of Four Cities ⋮ A full Bayesian approach to generalized maximum likelihood estimation of generalized extreme value distribution ⋮ Modelling dependence uncertainty in the extremes of Markov chain ⋮ Model misspecification in peaks over threshold analysis ⋮ Conditional extremes from heavy-tailed distributions: an application to the estimation of extreme rainfall return levels ⋮ A regional Bayesian POT model for flood frequency analysis ⋮ On the information in extreme measurements for parameter estimation ⋮ Assessment and propagation of input uncertainty in tree-based option pricing models ⋮ Bayesian estimation of intensity-duration-frequency curves and of the return period associated to a given rainfall event ⋮ A Bayesian analysis of clusters of extreme losses

Uses Software

• ismev

Cites Work

• Unnamed Item
• Extremes and related properties of random sequences and processes
• Extreme value analysis of environmental time series: an application to trend detection in ground-level ozone. With comments and a rejoinder by the author
• Models for the extremes of Markov chains
• An introduction to statistical modeling of extreme values

This page was built for publication: Anticipating Catastrophes through Extreme Value Modelling