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Modelling Spatial and Spatial-Temporal Data: A Bayesian Approach : A Bayesian Approach by Robert P. Haining, Guangquan Li is a nonfiction available to read on EtoBox.

What is Modelling Spatial and Spatial-Temporal Data: A Bayesian Approach : A Bayesian Approach about?

**Modelling Spatial and Spatial-Temporal Data: A Bayesian Approach** is aimed at statisticians and quantitative social, economic and public health students and researchers who work with small-area spatial and spatial-temporal data. It assumes a grounding in statistical theory up to the standard linear regression model. The book compares both hierarchical and spatial econometric modelling, providing both a reference and a teaching text with exercises in each chapter. The book provides a fully Bayesian, self-contained, treatment of the underlying statistical theory, with chapters dedicated to substantive applications. The book includes WinBUGS code and R code and all datasets are available online. Part I covers fundamental issues arising when modelling spatial and spatial-temporal data. Part II focuses on modelling cross-sectional spatial data and begins by describing exploratory methods that help guide the modelling process. There are then two theoretical chapters on Bayesian models and a chapter of applications. Two chapters follow on spatial econometric modelling, one describing different models, the other substantive applications. Part III discusses modelling spatial-temporal dat

Who reads Modelling Spatial and Spatial-Temporal Data: A Bayesian Approach : A Bayesian Approach?

Author

Robert P. Haining, Guangquan Li

Publisher

Chapman and Hall/CRC

Published

2020

Language

EN

ISBN

9781032175003

Category

nonfiction

Subjects

Mathematics, Stem