Bayesian Hierarchical Space-Time Models with Application to Significant Wave Height

• Κύριος συγγραφέας: Vanem, Erik (Συγγραφέας)
• Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
• Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
• Γλώσσα: English
• Έκδοση: Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2013.
• Σειρά: Ocean Engineering & Oceanography, 2
• Θέματα: Statistics.; Probabilities.; Geophysics.; Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences.; Probability Theory and Stochastic Processes.; Geophysics and Environmental Physics.

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...

Πίνακας περιεχομένων:

• 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.