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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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autor principal: Vanem, Erik (Autor)
Autor Corporativo: SpringerLink (Online service)
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2013.
Edición:1st ed. 2013.
Colección:Ocean Engineering & Oceanography, 2
Temas:
Statistics .
Probabilities.
Environmental sciences.
Physics.
Statistics in Engineering, Physics, Computer Science, Chemistry and Earth Sciences.
Probability Theory.
Environmental Physics.
Acceso en línea:Texto Completo
Tabla de Contenidos:
  • 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.

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