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...
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| Autor principal: | |
|---|---|
| Formato: | Livre numérique |
| Idioma: | Anglais |
| Publicado em: |
Berlin, Heidelberg :
Springer Berlin Heidelberg
[20..].
Cham : Springer Nature |
| Edição: | 1st ed. 2013. |
| coleção: | Ocean Engineering & Oceanography
2 |
| Assuntos: | |
| Acesso em linha: | Accès sur la plateforme de l'éditeur Accès sur la plateforme Istex Accès Université d'Orléans Accès INSA CVL |
| Nota: |
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 |
| LEADER | 04698nam a22003377a 4500 | ||
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| 009 | PPN176110542 | ||
| 020 | |a 9783642302534 | ||
| 041 | 0 | |a eng | |
| 082 | |a 519.5 | ||
| 100 | 1 | |a Vanem, Erik. | |
| 245 | 1 | 0 | |a Bayesian hierarchical space-time models with application to significant wave height |c by Erik Vanem. |
| 250 | |a 1st ed. 2013. | ||
| 260 | |a Berlin, Heidelberg : |b Springer Berlin Heidelberg. | ||
| 260 | |a Cham : |b Springer Nature, |c [20..]. | ||
| 490 | 0 | |a Ocean Engineering & Oceanography |v 2 |x 2194-640X | |
| 500 | |a Archives Springer e-books (Licence nationale) | ||
| 500 | |a Archives Springer e-books (Licence nationale) | ||
| 505 | 1 | |a 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 | |
| 506 | |a Accès en ligne pour les établissements français bénéficiaires des licences nationales | ||
| 506 | |a Accès soumis à abonnement pour tout autre établissement | ||
| 506 | |a Conditions particulières de réutilisation pour les bénéficiaires des licences nationales. https://www.licencesnationales.fr/springer-nature-ebooks-contrat-licence-ln-2017 | ||
| 520 | |a 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 structures and uncertainties in the data. This monograph is a research book and it is in some sense cross-disciplinary. The methodology itself is firmly rooted in the statistical research tradition, based on probability theory and stochastic processes. However, the methodology has been applied to a problem within physical oceanography, analysing data for significant wave height, which are of crucial importance to ocean engineering disciplines. Indeed, the statistical properties of significant wave height are important for the design, construction and operation of ships and other marine and coastal structures. Furthermore, the book addresses the question of whether climate change has an effect of the ocean wave climate, and if so what these effects might be. Thus, this book is an important contribution to the on-going debate on climate change, its implications and how to adapt to a changing climate, with a particular focus on the maritime industries and the marine environment. This book should be of general interest to anyone with an interest in statistical modelling of environmental processes, and in particular to those with a particular interest in the ocean wave climate. It is written on a level that should be understandable to everyone with a basic background in statistics or elementary mathematics, and an introduction to some basic concepts is given in appendices for the uninitiated reader. The intended readership incudes students and professionals involved in statistics, oceanography, ocean engineering, environmental research, climate sciences and risk assessment. Moreover, different stakeholders within the maritime industries such as design offices, classification societies, ship owners, yards and operators, flag states and intergovernmental agencies such as the IMO might find the results relevant | ||
| 650 | |a Statistiques | ||
| 776 | 0 | |t Bayesian Hierarchical Space-Time Models with Application to Significant Wave Height |b Texte imprimé |z 9783642302527 | |
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