Joint Bayesian model selection and parameter estimation of the generalized extreme value model with covariates using birth‐death Markov chain Monte Carlo

By S. El Adlouni, Taha B. M. J. Ouarda. 2009

51 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Demography, Finance

View Paper: https://www.semanticscholar.org/paper/38518460ee365facc8c9ba31ca3cd1c89bcf5296

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

1. C. Bracken
2. K. Holman
3. Hamid Moradkhani
4. Balaji Rajagopalan

In Demography

1. C. Bracken
2. K. Holman
3. Hamid Moradkhani
4. Balaji Rajagopalan

In Finance

1. C. Bracken
2. K. Holman
3. Hamid Moradkhani
4. Balaji Rajagopalan

Citations in the corpus

• A Bayesian Hierarchical Approach to Multivariate Nonstationary Hydrologic Frequency Analysis (2018, methodology): “El Adlouni and Ouarda (2009) and Ouarda and El Adlouni (2011) conduct simultaneous model selection and parameter estimation of a nonstationary GEV model using a birth-death Monte Carlo Markov chain (MCMC) procedure and reversible jump MCMC, respectively.”