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Usefulness of the Reversible Jump Markov Chain Monte
| Content Provider | Semantic Scholar |
|---|---|
| Author | Ribatet, Mathieu Sauquet, Eric Grésillon, J. – M. Ouarda, Taha B. M. J. |
| Copyright Year | 2006 |
| Abstract | Regional flood frequency analysis is a convenient way to reduce estimation uncertainty when few data are available at the gauging site. In this work, a model that allows a non null probability to a regional fixed shape parameter is presented. This methodology is integrated within a Bayesian framework and uses reversible jump techniques. The performance on stochastic data of this new estimator is compared to two other models: a conventional Bayesian analysis and the index flood approach. Results show that the proposed estimator is absolutely suited to regional estimation when only a few data is available at the target site. Moreover, unlike the index flood estimator, target site index flood error estimation seems to have less impact on Bayesian estimators. Some suggestions about configurations of the pooling groups are also presented to increase the performance of each estimator. |
| File Format | PDF HTM / HTML |
| Alternate Webpage(s) | http://www.lyon.cemagref.fr/hh/hydrologie/scientifiques/ribatet/publications/WRRRevJump.pdf |
| Alternate Webpage(s) | http://hal.archives-ouvertes.fr/docs/00/23/27/90/PDF/2006wr005525.pdf |
| Alternate Webpage(s) | http://arxiv.org/pdf/0802.0444v1.pdf |
| Alternate Webpage(s) | https://hal.archives-ouvertes.fr/file/index/docid/232790/filename/2006wr005525.pdf |
| Language | English |
| Access Restriction | Open |
| Subject Keyword | Frequency analysis Null Value Population Parameter Reversible-jump Markov chain Monte Carlo |
| Content Type | Text |
| Resource Type | Article |
