Titlebook: Bayesian Spatial Modelling with Conjugate Prior Models; Henning Omre,Torstein M. Fjeldstad,Ole Bernhard Fo Textbook 2024 The Editor(s) (if

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Selected Applications,f spatial continuous, event and mosaic variables and a mixture of them. The applications span epidemiology, basketball shooting, sub-surface geology and medical imaging. To appreciate the results of the studies, the reader must read the publication themselves.

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Computational Challenges,n Markov model, the basis function model, the kernel predictor and the integrated nested Laplace approximation are presented in the notation of the book. The focus is on their computational efficiency. Approximations are recommended for large studies with a large set of observations.

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Hasmat Malik,Atif Iqbal,Farhad Ilahi Bakhshthree types: continuous, event and mosaic. Motivating examples of modelling each of these spatial variable types are given. Simulation algorithms suitable for assessing this posterior model are presented in detail. Lastly, the notation in the book is established.

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Marrian H. Gebreselassie,Micheal Olusanyain a hierarchical modelling framework. The posterior pdfs for the most influential parameters can be analytically assessed because conjugate prior pdfs are assigned to them. Thus, estimates with credibility regions are available. The running examples are continued.

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