Titlebook: Statistical Modeling Using Bayesian Latent Gaussian Models; With Applications in Birgir Hrafnkelsson Book 2023 Springer Nature Switzerland

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Joshua Lovegrove,Stefan Siegerte.Clear and concise text.Includes supplementary material: Emergency care of pediatric orthopedic surgical emergencies is often provided by orthopedic surgeons who primarily treat adults. Pediatric Orthopedic Surgical Emergencies is designed to provide the essential information needed to safely evalu

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Bayesian Latent Gaussian Models,long with methods to infer the parameters of these models. The construction of prior densities for the latent parameters and the hyperparameters is described. Several examples are given to demonstrate how to apply models from these subclasses to real datasets.

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Improving Numerical Weather Forecasts by Bayesian Hierarchical Modelling,istical postprocessing methodology. In particular, we show that after fitting postprocessing parameters at each grid point by maximum likelihood estimation, a spatial smoothing of the parameter estimates is justified in a Bayesian hierarchical modelling context and offers improvements of out-of-sample forecasts.

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Bayesian Latent Gaussian Models,esent three subclasses within the class of Bayesian latent Gaussian models, namely, Bayesian Gaussian–Gaussian models, Bayesian latent Gaussian models with a univariate link function, and Bayesian latent Gaussian models with a multivariate link function. The structure of each subclass is described a

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Bayesian Modeling in Engineering Seismology: Ground-Motion Models,nt variables such as earthquake magnitude, distance from the earthquake, site effects, and more. The empirical GMM is expressed as a simple mathematical equation containing regression parameters to be inferred through a calibration of the model to a given dataset. Engineering seismologists strive fo