Bayesian inference with INLA Interest and a comprehensive up-to-date reading

and a comprehensive up-to-date reading list is included to guide the trainee to areas of further reading

a companion flashcard app also incorporates the key vocabulary for study and practice on-the-go

Enjoy 48 pages of sticker activities and colouring with Anna

• Covers biofuel properties

clear explanations and worked examples

Bayesian inference with INLA Interest and a comprehensive up-to-date readingThe integrated nested Laplace approximation (INLA) is a recent computational method that can fit Bayesian models in a fraction of the time required by typical Markov chain Monte Carlo (MCMC) methods. INLA focuses on marginal inference on the model parameters of latent Gaussian Markov random fields models and exploits conditional independence properties in the model for computational speed. Bayesian Inference with INLA provides a description of INLA