Parameter optimization and uncertainty assessment for rainfall frequency modeling using an adaptive Metropolis-Hastings algorithm
A new parameter optimization and uncertainty assessment procedure using the Bayesian inference with an adaptive Metropolis-Hastings (AM-H) algorithm is presented for extreme rainfall frequency modeling. An efficient Markov chain Monte Carlo sampler is adopted to explore the posterior distribution of...
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Détails bibliographiques
| Publié dans: | Water science and technology : a journal of the International Association on Water Pollution Research. - 1986. - 83(2021), 5 vom: 16. März, Seite 1085-1102
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| Auteur principal: |
Liu, Xingpo
(Auteur) |
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| Autres auteurs: |
Xia, Chengfei,
Tang, Yifan,
Tu, Jiayang,
Wang, Huimin |
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| Format: | Article en ligne
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| Langue: | English |
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| Publié: |
2021
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| Accès à la collection: | Water science and technology : a journal of the International Association on Water Pollution Research
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| Sujets: | Journal Article |
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