Bayesian hierarchical space-time models with application to significant wave height
This book provides an example of a thorough statistical treatment in space and time of ocean wave data. It is demonstrated how the flexible framework of Bayesian hierarchical space-time models can be applied to oceanographic processes such as significant wave height in order to describe dependence s...
Uloženo v:
| Hlavní autor: | |
|---|---|
| Médium: | Livre numérique |
| Jazyk: | Anglais |
| Vydáno: |
Berlin, Heidelberg :
Springer Berlin Heidelberg
[20..].
Cham : Springer Nature |
| Vydání: | 1st ed. 2013. |
| Edice: | Ocean Engineering & Oceanography
2 |
| Témata: | |
| On-line přístup: | Accès sur la plateforme de l'éditeur Accès sur la plateforme Istex Accès Université d'Orléans Accès INSA CVL |
| Poznámka: |
Archives Springer e-books (Licence nationale) Archives Springer e-books (Licence nationale) |
| Autres localisations: | Voir dans le Sudoc |
| Edition sous un autre format: | • Bayesian Hierarchical Space-Time Models with Application to Significant Wave Height, Texte imprimé, 9783642302527 |
Obsah:
- Preface Acronyms 1.Introduction and Background 2.Literature Survey on StochasticWave Models 3.A Bayesian Hierarchical Space-Time Model for Significant Wave Height 4.Including a Log-Transform of the Data 6.Bayesian Hierarchical Modelling of the Ocean Windiness 7.Application: Impacts on Ship Structural Loads 8.Case study: Modelling the Effect of Climate Change on the World s Oceans 9.Summary and Conclusions A.Markov Chain Monte Carlo Methods B.Extreme Value Modelling C.Markov Random Fields D.Derivation of the Full Conditionals of the Bayesian Hierarchical Space-Time Model for Significant Wave Height E.Sampling from a Multi-normal Distribution