000 04390nam a22003735i 4500
001 304902
003 MX-SnUAN
005 20160429155925.0
007 cr nn 008mamaa
008 150903s2013 gw | o |||| 0|eng d
020 _a9783642302534
_99783642302534
024 7 _a10.1007/9783642302534
_2doi
035 _avtls000359230
039 9 _a201509031020
_bVLOAD
_c201405070243
_dVLOAD
_y201402191550
_zstaff
040 _aMX-SnUAN
_bspa
_cMX-SnUAN
_erda
050 4 _aQA276-280
100 1 _aVanem, Erik.
_eautor
_9343856
245 1 0 _aBayesian Hierarchical Space-Time Models with Application to Significant Wave Height /
_cby Erik Vanem.
264 1 _aBerlin, Heidelberg :
_bSpringer Berlin Heidelberg :
_bImprint: Springer,
_c2013.
300 _axx, 262 páginas 85 ilustraciones, 14 ilustraciones en color.
_brecurso en línea.
336 _atexto
_btxt
_2rdacontent
337 _acomputadora
_bc
_2rdamedia
338 _arecurso en línea
_bcr
_2rdacarrier
347 _aarchivo de texto
_bPDF
_2rda
490 0 _aOcean Engineering & Oceanography,
_x2194-6396 ;
_v2
500 _aSpringer eBooks
505 0 _aPreface -- 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 _aThis 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.
590 _aPara consulta fuera de la UANL se requiere clave de acceso remoto.
710 2 _aSpringerLink (Servicio en línea)
_9299170
776 0 8 _iEdición impresa:
_z9783642302527
856 4 0 _uhttp://remoto.dgb.uanl.mx/login?url=http://dx.doi.org/10.1007/978-3-642-30253-4
_zConectar a Springer E-Books (Para consulta externa se requiere previa autentificación en Biblioteca Digital UANL)
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999 _c304902
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