activity
20172026
most citedSpatial Models with the Integrated Nested Laplace Approximation within Markov Chain Monte Carlo

3 citations · 7 across the 7 of their papers we have counts for

collaborators

9 papers

stat.ME2026

Efficient model exploration with the integrated nested Laplace approximation

Héctor López-Gómez, Virgilio Gómez-Rubio, Gonzalo García-Donato

Model and variable selection are important topics in Bayesian inference. In particular, the selection of different fixed, random effects and hyperparameters in hierarchical models…

stat.AP2022

Improving radiation dose estimation using the gamma-H2AX biomarker

Dorota Młynarczyk, Pedro Puig, Carmen Armero +3

To predict the health effects of accidental or therapeutic radiation exposure, one must estimate the radiation dose that person received. A well-known ionising radiation biomarker,…

stat.ME2022

Fitting Double Hierarchical Models with the Integrated Nested Laplace Approximation

Mabel Morales-Otero, Virgilio Gómez-Rubio, Vicente Núñez-Antón

Double hierarchical generalized linear models (DHGLM) are a family of models that are flexible enough as to model hierarchically the mean and scale parameters. In a Bayesian framew…

stat.AP2021

Bayesian hierarchical nonlinear modelling of intra-abdominal volume during pneumoperitoneum for laparoscopic surgery

Gabriel Calvo, Carmen Armero, Virgilio Gómez-Rubio +1

Laparoscopy is an operation carried out in the abdomen or pelvis through small incisions with external visual control by a camera. This technique needs the abdomen to be insufflate…

stat.CO2021

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…

stat.CO2019★ 3 cited

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…

stat.CO2019

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…

stat.AP2019★ 1 cited

Correlated functional models with derivative information for modeling MFS data on rock art paintings

Gabriel Riutort-Mayol, Virgilio Gómez-Rubio, José Luis Lerma +1

Microfading Spectrometry (MFS) is a method for assessing light sensitivity color (spectral) variations of cultural heritage objects. Each measured point on the surface gives rise t…

stat.CO2017★ 3 cited

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…