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OverviewThis book provides an example of a thorough statistical treatment of ocean wave data in space and time. It demonstrates 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 partly cross-disciplinary. The methodology itself is firmly rooted in the statistical research tradition, based on probability theory and stochastic processes. However, that methodology has been applied to a problem in the field of physical oceanography, analyzing data for significant wave height, which is 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 that effect might be. Thus, this book is an important contribution to the ongoing 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 value to anyone with an interest in the statistical modelling of environmental processes, and in particular to those with an 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 provided in the appendices for the uninitiated reader. The intended readership includes students and professionals involved in statistics, oceanography, ocean engineering, environmental research, climate sciences and risk assessment. Moreover, the book’s findings are relevant for various stakeholders in the maritime industries such asdesign offices, classification societies, ship owners, yards and operators, flag states and intergovernmental agencies such as the IMO. Full Product DetailsAuthor: Erik Vanem , Elzbieta Maria Bitner-Gregersen , Christopher K. WiklePublisher: Springer-Verlag Berlin and Heidelberg GmbH & Co. KG Imprint: Springer-Verlag Berlin and Heidelberg GmbH & Co. K Edition: Softcover reprint of the original 1st ed. 2013 Volume: 2 Dimensions: Width: 15.50cm , Height: 1.50cm , Length: 23.50cm Weight: 4.336kg ISBN: 9783662521977ISBN 10: 3662521970 Pages: 262 Publication Date: 23 August 2016 Audience: Professional and scholarly , Professional & Vocational Format: Paperback Publisher's Status: Active Availability: Manufactured on demand  We will order this item for you from a manufactured on demand supplier. Table of ContentsPreface.- 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.ReviewsThe core of this book is the development of a space-time model for significant wave heights. ... the models are carefully constructed and executed. They should serve as a useful guide to anyone who wishes to experiment with similar techniques and I recommend this book to researchers interested in exploring time series data by Bayesian methods. (George Z. Forristall, Journal of Ocean Engineering and Marine Energy, Vol. 1, 2015) Author InformationTab Content 6Author Website:Countries AvailableAll regions |
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