| 期刊全稱 | Bayesian Hierarchical Space-Time Models with Application to Significant Wave Height | | 影響因子2023 | Erik Vanem | | 視頻video | http://file.papertrans.cn/182/181846/181846.mp4 | | 發(fā)行地址 | The monograph addresses modelling of ocean wave climate in space and time.Of interest to everyone with an interest in climate research and the effects of climate change.Focus on long-term temporal tre | | 學(xué)科分類 | Ocean Engineering & Oceanography | | 圖書封面 |  | | 影響因子 | .This 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 c | | Pindex | Book 2013 |
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