Review of Bayesian Regression Modelling with INLA by Xiaofeng Wang, Yu Ryan Yue, and Julian J. Faraway

  • Kathryn MorrisonEmail author
Book Review

For many statisticians, the use of Bayesian methods implies a journey into all of the associated challenges of writing bespoke MCMC code. Perhaps worse, for applied statistical practitioners, Bayesian methods imply the use of ancient, unsupported WinBUGS or OpenBUGS software. Newer implementations such as JAGS and Stan have alleviated significant amounts of suffering, but since its 2009 seminal paper Rue et al. (2009), INLA has broken the synonymy of Bayes and MCMC. Adoption has been highest in fields where computational challenges are the most severe, notably spatial and temporal modelling.

In Bayesian Regression Modelling with INLA, Wang, Yue and Faraway deliver a first, much-needed general text on INLA that is not concentrated on spatial modelling. They begin with a practical refresher on Bayesian inference, sufficient for anyone rusty but not a substitute for original study, for which they refer the audience to fundamental resources like Gelman’s BDA Gelman et al. (2013). For any...


  1. Rue H, Martino S, Chopin N. Approximate Bayesian inference for latent Gaussian models by using integrated nested Laplace approximations. Journal of the royal statistical society: Series b (statistical methodology). 2009 Apr 1;71(2):319-92.Google Scholar
  2. Gelman, A., Stern, H.S., Carlin, J.B., Dunson, D.B., Vehtari, A. and Rubin, D.B., 2013. Bayesian Data Analysis. Chapman and Hall/CRC.Google Scholar
  3. Lunn D, Jackson C, Best N, Spiegelhalter D, Thomas A. The BUGS book: A practical introduction to Bayesian analysis. Chapman and Hall/CRC; 2012 Oct 2.Google Scholar
  4. Hoffman MD, Gelman A. The No-U-turn sampler: adaptively setting path lengths in Hamiltonian Monte Carlo. Journal of Machine Learning Research. 2014 Apr 1;15(1):1593-623.Google Scholar

Copyright information

© International Biometric Society 2018

Authors and Affiliations

  1. 1.Co-founder and CTO, Precision Analytics IncMontrealCanada
  2. 2.Department of Epidemiology and BiostatisticsMcGill UniversityMontrealCanada

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