Bayesian Hierarchical Space-time Models With Application to Significant Wave Height Hardback - 2013
by Vanem, Erik/ Bitner-gregersen, Elzbieta Maria (Foreward By)
- New
- Hardback
Standard delivery: 7 to 14 days
Details
- Title Bayesian Hierarchical Space-time Models With Application to Significant Wave Height
- Author Vanem, Erik/ Bitner-gregersen, Elzbieta Maria (Foreward By)
- Binding Hardback
- Condition New
- Pages 262
- Volumes 1
- Language ENG
- Publisher Springer Verlag
- Publication date 2013
- Illustrated Yes
- Features Illustrated
- Bookseller's Inventory # x-3642302521
- ISBN 9783642302527 / 3642302521
- Weight 1.27 lbs (0.58 kg)
- Dimensions 9.21 x 6.14 x 0.69 in (23.39 x 15.60 x 1.75 cm)
- Category Mathematics
- Dewey Decimal Code 519.2
- Quantity available 2
About Revaluation Books Devon, United Kingdom
General bookseller of both fiction and non-fiction.
Reader reviews for Bayesian Hierarchical Space-time Models With Application to Significant Wave Height
Write a review for this book
Important Terms and Guidelines
- Please focus on the book’s content and context. Also, add any personal comments as to how you enjoyed the book. Substantiate your likes and dislikes. You may make comparisons to other books.
- Reviews must be at least 140 characters in length.
- Please do not reveal critical plot elements.
- This is not a help line. Contact customer support if you need help.
Your review must not include:
- Obscenities, discriminatory language, or other insulting language not suitable for public domain
- Advertisements, “spam” content, or references to other products, offers or websites.
- Email addresses, URLs, phone numbers, physical addresses or other contact information.
- Overly critical comments about other reviews or reviewers
- Time-sensitive material (i.e. promotional tours, seminars, lectures, etc.)
- Availability, price, or alternative ordering/shipping information
From the publisher
From the rear cover
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 hasan 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.