Bayesian inference with INLA - Paperback
Bayesian inference with INLA - Paperback
Description
by Virgilio Gomez-Rubio (Author)
The Integrated Nested Laplace Approximation (INLA) is a popular method for approximate Bayesian inference. This book provides an introduction to the underlying INLA methodology and practical guidance on how to fit different models with R-INLA and R. This covers a wide range of applications, such as multilevel models, spatial models and survival
Author Biography
Virgilio Gómez-Rubio is associate professor in the Department of Mathematics, School of Industrial Engineering, Universidad de Castilla-La Mancha, Albacete, Spain. He has developed several packages on spatial and Bayesian statistics that are available on CRAN, as well as co-authored books on spatial data analysis and INLA including Advanced Spatial Modeling with Stochastic Partial Differential Equations Using R and INLA (CRC Press, 2019).
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