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20140310151458.0 |
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131010s2013 gw | s |||| 0|eng d |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER |
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| International Standard Book Number |
9783642302534 |
|
978-3-642-30253-4 |
| 050 #4 - LIBRARY OF CONGRESS CALL NUMBER |
|---|
| Classification number |
QA276-280 |
| 082 04 - DEWEY DECIMAL CLASSIFICATION NUMBER |
|---|
| Classification number |
519.5 |
| Edition number |
23 |
| 264 #1 - |
|---|
| -- |
Berlin, Heidelberg : |
| -- |
Springer Berlin Heidelberg : |
| -- |
Imprint: Springer, |
| -- |
2013. |
| 912 ## - |
|---|
| -- |
ZDB-2-SMA |
| 100 1# - MAIN ENTRY--PERSONAL NAME |
|---|
| Personal name |
Vanem, Erik. |
| Relator term |
author. |
| 245 10 - IMMEDIATE SOURCE OF ACQUISITION NOTE |
|---|
| Title |
Bayesian Hierarchical Space-Time Models with Application to Significant Wave Height |
| Medium |
[electronic resource] / |
| Statement of responsibility, etc |
by Erik Vanem. |
| 300 ## - PHYSICAL DESCRIPTION |
|---|
| Extent |
XX, 262 p. 85 illus., 14 illus. in color. |
| Other physical details |
online resource. |
| 440 1# - SERIES STATEMENT/ADDED ENTRY--TITLE |
|---|
| Title |
Ocean Engineering & Oceanography, |
| International Standard Serial Number |
2194-6396 ; |
| Volume number/sequential designation |
2 |
| 505 0# - FORMATTED CONTENTS NOTE |
|---|
| Formatted contents note |
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. |
| 520 ## - SUMMARY, ETC. |
|---|
| Summary, etc |
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 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name as entry element |
Statistics. |
|
|---|
| Topical term or geographic name as entry element |
Distribution (Probability theory). |
|
|---|
| Topical term or geographic name as entry element |
Statistics. |
|
|---|
| Topical term or geographic name as entry element |
Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences. |
|
|---|
| Topical term or geographic name as entry element |
Probability Theory and Stochastic Processes. |
|
|---|
| Topical term or geographic name as entry element |
Geophysics and Environmental Physics. |
| 710 2# - ADDED ENTRY--CORPORATE NAME |
|---|
| Corporate name or jurisdiction name as entry element |
SpringerLink (Online service) |
| 773 0# - HOST ITEM ENTRY |
|---|
| Title |
Springer eBooks |
| 776 08 - ADDITIONAL PHYSICAL FORM ENTRY |
|---|
| Display text |
Printed edition: |
| International Standard Book Number |
9783642302527 |
| 856 40 - ELECTRONIC LOCATION AND ACCESS |
|---|
| Uniform Resource Identifier |
http://dx.doi.org/10.1007/978-3-642-30253-4 |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) |
|---|
| Source of classification or shelving scheme |
|
| Item type |
E-Book |
