Statistical Modeling Using Bayesian Latent Gaussian Models
Produktnummer:
182c2ce5ce2b71464997cd524d71858149
Themengebiete: | Bayesian hierarchical models Environmental sciences Gaussian processes Geophysics Physical-statistical modeling Posterior inference Prior distributions Sea-level rise Statistical application in environmental sciences Statistical modeling |
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Veröffentlichungsdatum: | 09.11.2024 |
EAN: | 9783031397936 |
Sprache: | Englisch |
Seitenzahl: | 251 |
Produktart: | Kartoniert / Broschiert |
Herausgeber: | Hrafnkelsson, Birgir |
Verlag: | Springer International Publishing |
Untertitel: | With Applications in Geophysics and Environmental Sciences |
Produktinformationen "Statistical Modeling Using Bayesian Latent Gaussian Models"
This book focuses on the statistical modeling of geophysical and environmental data using Bayesian latent Gaussian models. The structure of these models is described in a thorough introductory chapter, which explains how to construct prior densities for the model parameters, how to infer the parameters using Bayesian computation, and how to use the models to make predictions. The remaining six chapters focus on the application of Bayesian latent Gaussian models to real examples in glaciology, hydrology, engineering seismology, seismology, meteorology and climatology. These examples include: spatial predictions of surface mass balance; the estimation of Antarctica’s contribution to sea-level rise; the estimation of rating curves for the projection of water level to discharge; ground motion models for strong motion; spatial modeling of earthquake magnitudes; weather forecasting based on numerical model forecasts; and extreme value analysis of precipitation on a high-dimensional grid. The book is aimed at graduate students and experts in statistics, geophysics, environmental sciences, engineering, and related fields.

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