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Bayesian Spatial Modelling with Conjugate Prior Models by Henning Omre, Torstein M. Fjeldstad, Ole Bernhard Forberg is a nonfiction available to read on EtoBox.

What is Bayesian Spatial Modelling with Conjugate Prior Models about?

This book offers a comprehensive overview of statistical methodology for modelling and evaluating spatial variables useful in a variety of applications. These spatial variables fall into three categories: continuous, like terrain elevation; events, like tree locations; and mosaics, like medical images. Definitions and discussions of random field models are included for each of these three previously mentioned spatial variable types. Moreover, the readers will have access to algorithms suitable for applying this methodology in practical problem solving, and the computational efficiency of these algorithms are discussed. The presentation is made in a consistent predictive Bayesian framework, which allows separate modelling of the observation acquisition procedure, as a likelihood model, and of the spatial variable characteristics, as a prior spatial model. The likelihood and prior models uniquely define the posterior spatial model, which provides the basis for spatial simulations, spatial predictions with associated precisions, and model parameter inference. The emphasis is on Bayesian spatial modelling with conjugate pairs of likelihood and prior models that are analytically tractab

Who reads Bayesian Spatial Modelling with Conjugate Prior Models?

Author

Henning Omre, Torstein M. Fjeldstad, Ole Bernhard Forberg

Publisher

Springer Nature Switzerland AG

Published

2024

Language

EN

ISBN

9783031654176

Category

nonfiction

Subjects

Mathematics, Stem