Anticipating catastrophes through extreme value modelling

By Stuart Coles, Luis Raúl Pericchi. 2003

194 citations recorded by the source corpus.

Subfields: Economics and Econometrics, Finance, Global and Planetary Change

View Paper: https://www.semanticscholar.org/paper/a6faf125805441e6f019fbd76e014eff56c282e5

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Citations in the corpus

Bayesian MCMC flood frequency analysis with historical information (2005, methodology): “Papers and books describe approximate confidence intervals for quantiles of distributions used in hydrology (USWRC, 1982; Stedinger, 1983a; Kite, 1988; Chowdhury and Stedinger, 1991; Stedinger et al., 1993; Bobee and Ashkar, 1991; Ashkar and Ouarda, 1998; Whitley and Hromadka, 1999; Cohn et al., 200”
OR/MS research in disaster operations management (2006, unknown): “Mitigation: Coles and Pericchi (2003), Englehardt (2002), Hsieh (2004), Leung et al.”
An application of Bayesian analysis and Markov chain Monte Carlo methods to the estimation of a regional trend in annual maxima (2006, background): “…1998; Lu and Berliner, 1999; Perreault et al., 1999, 2000a, 2000b, 2000c; Thyer and Kuczera, 2000, 2003a, 2003b; Wang, 2001; Thyer et al., 2002; Coles and Pericchi, 2003; Coles et al., 2003; Parent and Bernier, 2003; Perreault and Fortin, 2003; Tapsoba et al., 2004; Moyeed and Clarke, 2005;…”
A fully probabilistic approach to extreme rainfall modeling (2003, unknown): “in each of two seasons ( Coles and Pericchi, 2001 ).”
Conditional extremes from heavy-tailed distributions: an application to the estimation of extreme rainfall return levels (2010, background): “Such seasonal approaches have already been considered in Bayesian models (Coles and Pericchi 2003; Coles et al. 2003).”
Statistical analysis of extreme events in a non-stationary context via a Bayesian framework: case study with peak-over-threshold data (2006, unknown): “Among them, Bayesian analysis recently received attention, thanks to advances in computational and numerical tools (Coles and Powell 1996; Coles and Tawn 1996; Coles and Pericchi 2003; Coles et al. 2003; Diebolt et al. 2003; Parent and Bernier 2003).”
Bayesian analysis of extreme events with threshold estimation (2004, background): “Coles and Pericchi (2003) showed that this leads to more sensible solutions to real extremes data problems than plug-in estimation.”
A regional Bayesian POT model for flood frequency analysis (2007, methodology): “The Bayesian concepts have already been applied with success to the regional frequency analysis of extreme rainfalls (Coles and Pericchi, 2003) and floods (Madsen and Rosbjerg, 1997; Northrop, 2004).”
100-Year Return Value Estimates for Ocean Wind Speed and Significant Wave Height from the ERA-40 Data (2005, background): “The reader, however, should be aware that there are people in the extremes community that (in certain situations) advocate fitting the GPD rather than the exponential even when the exponential seems a plausible model (see Coles and Pericchi 2003).”
Joint Bayesian model selection and parameter estimation of the generalized extreme value model with covariates using birth‐death Markov chain Monte Carlo (2009, background): “This approach is not recommended for extreme model selection [Coles and Pericchi, 2003].”
Model misspecification in peaks over threshold analysis (2010, unknown): “Coles and Pericchi (2003) apply a Bayesian approach to the point process representation [Smith (1989)], which is essentially equivalent to fitting the generalized Pareto distribution.”
Optimization models in emergency logistics: A literature review (2012, methodology): “Research addresses those challenges through the use of statistical and probabilistic models [16,69], queuing theory [3], simulation [33,55], decision theory [17,62], fuzzy methods [21,37], and most commonly, optimization methods (will be discussed in this paper).”