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Bayesian regression modeling with INLA. (English) Zbl 1420.62005

Chapman & Hall/CRC Computer Science & Data Analysis Series. Boca Raton, FL: CRC Press (ISBN 978-1-4987-2725-9/hbk; 978-1-351-16575-4/ebook). xii, 312 p. (2018).
INLA stands for integrated nested Laplace approximations. This method is used for fitting a broad class of Bayesian models. A very simple and over-examined model is the least square method. The extension of this method is a class of statistical models like GLM/GAM/GLMM/GAMM considered here.
The INLA approach is not a rival/competitor/replacement to/of MCMC, just a better option of GLMs. R scripts for the class of INLA method are given at the web-page http://julianfaraway.github.io/brinla. Help for running the R scripts can be found here. It is a must-have book for everyone interested in the Bayesian regression method and INLA.

MSC:

62-01 Introductory exposition (textbooks, tutorial papers, etc.) pertaining to statistics
62J05 Linear regression; mixed models
62F15 Bayesian inference
62-04 Software, source code, etc. for problems pertaining to statistics
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