11 citations · 16 across the 6 of their papers we have counts for
9 papers
A framework for estimating and visualising excess mortality during the COVID-19 pandemic
Garyfallos Konstantinoudis, Virgilio Gómez-Rubio, Michela Cameletti +3
COVID-19 related deaths underestimate the pandemic burden on mortality because they suffer from completeness and accuracy issues. Excess mortality is a popular alternative, as it c…
Bayesian analysis of population health data
Dorota Młynarczyk, Carmen Armero, Virgilio Gómez-Rubio +1
The analysis of population-wide datasets can provide insight on the health status of large populations so that public health officials can make data-driven decisions. The analysis…
Bayesian survival analysis with BUGS
Danilo Alvares, Elena Lázaro, Virgilio Gómez-Rubio +1
Survival analysis is one of the most important fields of statistics in medicine and the biological sciences. In addition, the computational advances in the last decades have favour…
A Bayesian Multilevel Random-Effects Model for Estimating Noise in Image Sensors
Gabriel Riutort-Mayol, Virgilio Gómez-Rubio, Ángel Marqués-Mateu +2
Sensor noise sources cause differences in the signal recorded across pixels in a single image and across multiple images. This paper presents a Bayesian approach to decomposing and…
Bayesian Multivariate Spatial Models for Lattice Data with INLA
Francisco Palmi-Perales, Virgilio Gomez-Rubio, Miguel A. Martinez-Beneito
The INLAMSM package for the R programming language provides a collection of multivariate spatial models for lattice data that can be used with package INLA for Bayesian inference.…
Approximate Bayesian inference for multivariate point pattern analysis in disease mapping
Francisco Palmi-Perales, Virgilio Gomez-Rubio, Gonzalo Lopez-Abente +3
We present a novel approach for the analysis of multivariate case-control georeferenced data using Bayesian inference in the context of disease mapping, where the spatial distribut…
Mixture model fitting using conditional models and modal Gibbs sampling
Héctor Gómez-López, Virgilio Gómez-Rubio
Mixture models are a convenient way of modeling data using a convex combination of different parametric distributions. A new algorithm based on Gibbs sampling is used to approximat…
Estimating Spatial Econometrics Models with Integrated Nested Laplace Approximation
Virgilio Gomez-Rubio, Roger S. Bivand, Håvard Rue
Integrated Nested Laplace Approximation provides a fast and effective method for marginal inference on Bayesian hierarchical models. This methodology has been implemented in the R-…
Markov Chain Monte Carlo with the Integrated Nested Laplace Approximation
Virgilio Gómez-Rubio, Håvard Rue
The Integrated Nested Laplace Approximation (INLA) has established itself as a widely used method for approximate inference on Bayesian hierarchical models which can be represented…