3 citations · 7 across the 7 of their papers we have counts for
4 papers · 1 filter
Importance Sampling with the Integrated Nested Laplace Approximation
Martin Outzen Berild, Sara Martino, Virgilio Gómez-Rubio +1
The Integrated Nested Laplace Approximation (INLA) is a deterministic approach to Bayesian inference on latent Gaussian models (LGMs) and focuses on fast and accurate approximation…
Missing data analysis and imputation via latent Gaussian Markov random fields
Virgilio Gómez-Rubio, Michela Cameletti, Marta Blangiardo
In this paper we recast the problem of missing values in the covariates of a regression model as a latent Gaussian Markov random field (GMRF) model in a fully Bayesian framework. O…
Bayesian model averaging with the integrated nested Laplace approximation
Virgilio Gómez-Rubio, Roger S. Bivand, Håvard Rue
The integrated nested Laplace approximation (INLA) for Bayesian inference is an efficient approach to estimate the posterior marginal distributions of the parameters and latent eff…
Spatial Models with the Integrated Nested Laplace Approximation within Markov Chain Monte Carlo
Virgilio Gómez-Rubio, Francisco Palmí-Perales
The Integrated Nested Laplace Approximation (INLA) is a convenient way to obtain approximations to the posterior marginals for parameters in Bayesian hierarchical models when the l…