Bayesian Inference for Extremes: Accounting for the Three Extremal Types
By Alec Stephenson, Jonathan A. Tawn. 2004
83 citations recorded by the source corpus.
Subfields: Economics and Econometrics, Finance
View Paper: https://www.semanticscholar.org/paper/1a43e0a9b5846f37947429c67f2163591ec9ae12
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Economics and Econometrics
- M. Charras-Garrido
- Daniel Cooley
- D. Nychka
- Uk
- Pascal Lezaud
- Philippe Naveau
- Nicola London
- Paul Northrop
In Finance
- M. Charras-Garrido
- Daniel Cooley
- D. Nychka
- Uk
- Pascal Lezaud
- Philippe Naveau
- Nicola London
- Paul Northrop
Citations in the corpus
- Extreme Value Analysis: an Introduction (2013, background): “For example, Stephenson and Tawn (2004) propose to estimate the parameters of the GPD distribution given the domain of attraction i.e. with constraints on parameter γ .”
- Bayesian Spatial Modeling of Extreme Precipitation Return Levels (2007, background): “Although there have been several studies using Bayesian methods in extremes (e.g., Smith and Naylor 1987; Coles and Tawn 1996a; Bottolo, Consonni, Dellaportas, and Lijoi 2003; Stephenson and Tawn 2005) only a few have built models that borrowed strength across different spatial locations.”
- Posterior propriety in Bayesian extreme value analyses using reference priors (2015, methodology): “Alternatively, a Bayesian approach (Coles, 2001; Coles and Powell, 1996; Stephenson and Tawn, 2004) can avoid conditions on the value of ξ and performs predictive inference about future observations naturally and conveniently using Markov chain Monte Carlo (MCMC) output.”