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Bayesian hierarchical space-time mod...

Vanem, Erik.

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Bayesian hierarchical space-time models with application to significant wave height /

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Bayesian hierarchical space-time models with application to significant wave height // Erik Vanem.
作者:	Vanem, Erik.
出版者:	Heidelverg :Springer Verlag, : c2013.,
面頁冊數:	xx, 262 p. :ill. (some col.) ;24 cm.
標題:	Water waves - Mathematical models. -
ISBN:	9783642302527 (hbk.) :
ISSN:	21946396

Bayesian hierarchical space-time models with application to significant wave height /
Vanem, Erik.

Bayesian hierarchical space-time models with application to significant wave height /Erik Vanem. - Heidelverg :Springer Verlag,c2013. - xx, 262 p. :ill. (some col.) ;24 cm. - Ocean Engineering & Oceanography,volume 2 2194-6396 ;. - Ocean engineering & oceanography ;v.2 .

Includes bibliographical references.

Introduction and background --

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 inorder 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 includes 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 designoffices, classification societies, ship owners, yards and operators, flag states and intergovernmental agencies suchas the IMO might find the results relevant.

ISBN: 9783642302527 (hbk.) :EUR84.99

ISSN: 21946396Subjects--Topical Terms:

668635
Water waves
--Mathematical models.

LC Class. No.: QA927 / V36z 2013

Dewey Class. No.: 519.2

Bayesian hierarchical space-time models with application to significant wave height /
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050 # 4 $a QA927 $b V36z 2013
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100 1 $a Vanem, Erik. $3 2021718
245 1 0 $a Bayesian hierarchical space-time models with application to significant wave height / $c Erik Vanem.
260 # $a Heidelverg : $b Springer Verlag, $c c2013.
300 $a xx, 262 p. : $b ill. (some col.) ; $c 24 cm.
490 1 0 $a Ocean Engineering & Oceanography, $x 2194-6396 ; $v volume 2
504 $a Includes bibliographical references.
505 0 # $t Introduction and background -- $t Literature survey on stochastic wave models -- $t A Bayesian Hierarchical Space-Time Model for significant wave height -- $t Including a log-transform of the data -- $t Bayesian Hierarchical modelling of the ocean windiness -- $t Application : impacts on ship structural loads -- $t Case study : modelling the effect of climate change on the world's oceans -- $t Summary and Conclusions -- $t Markov Chain Monte Carlo methods -- $t Extreme value modelling -- $t Markov random fields -- $t Derivation of the full conditionals of the Bayesian Hierarchical Space-Time Model for significant wave height -- $t Sampling from a multi-normal distribution.
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 inorder 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 includes 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 designoffices, classification societies, ship owners, yards and operators, flag states and intergovernmental agencies suchas the IMO might find the results relevant.
650 # 0 $a Water waves $x Mathematical models. $3 668635
830 0 $a Ocean engineering & oceanography ; $v v.2 $3 2021719