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Advanced Spatial Modeling with Stochastic Partial Differential Equations Using R and Inla

Contributor(s): Krainski, Elias (Author), Gómez-Rubio, Virgilio (Author), Bakka, Haakon (Author), Lenzi, Amanda (Author), Castro-Camilo, Daniela (Author), Simpson, Daniel (Author), Lindgren, Finn (Author), Rue, Håvard (Author)

ISBN: 9780367570644

Publisher: CRC Press

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Pub Date: June 30, 2020

Dewey: 519.22

Lexile Code: 0000

Target Age Group: NA to NA

Physical Info: 0.70" H x 9.10" L x 5.90" W ( 1.05 lbs) 284 pages

Descriptions, Reviews, etc.

Description: The Integrated Nested Laplace Approximation is a popular method for approximate Bayesian inference. INLA is an alternative to other methods for Bayesian inference, such as Markov Chain Monte Carlo, that are more computationally demanding. In addition, the R-INLA package for the R statistical software provides a way to fit such models in practice

Review Quotes:

"Besides the epidemiological perspective, they have also tried to address many of the applied issues in disease mapping practice, which may make this book different from others previously published on this topic. To further facilitate understanding, the authors have made all code and data used in their examples available. A GitHub repository has also been created for hosting the book's online supplementary material. Thus, one can make use of the functionalities that GitHub deploys for their repositories, such as highlighting points to be clarified by the authors. As a great novelty of the book, the online material may enable readers to have direct access to most of the statistical/computing details that there is not enough room to fully explain within the book." Sada Nand Dwivedi, ICSB News

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