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20112025
most citedInferences in Bayesian variable selection problems with large model spaces

5 citations · 10 across the 4 of their papers we have counts for

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stat.ME2025

A multivariate spatial model for ordinal survey-based data

Miguel Ángel Beltrán-Sánchez, Miguel Ángel Martínez-Beneito, Ana Corberán-Vallet

Health surveys provide valuable information for monitoring population health, identifying risk factors and informing public health policies. Most of the questions included are code…

stat.ME2025

A proposal for homoscedastic modelling with conditional auto-regressive distributions

Miguel A. Martinez-Beneito, Aritz Adín, Tomás Goicoa +1

Conditional auto-regressive (CAR) distributions are widely used to induce spatial dependence in the geographic analysis of areal data. These distributions establish multivariate de…

stat.ME2024

Bayesian modeling of spatial ordinal data from health surveys

Miguel Ángel Beltrán Sánchez, Miguel Ángel Martínez Beneito, Ana Corberán Vallet

Health surveys allow exploring health indicators that are of great value from a public health point of view and that cannot normally be studied from regular health registries. Thes…

stat.ME20165 cited

Bayesian variable selection in high dimensional problems without assumptions on prior model probabilities

James O. Berger, Gonzalo Garcia-Donato, Miguel A. Martinez-Beneito +1

We consider the problem of variable selection in linear models when , the number of potential regressors, may exceed (and perhaps substantially) the sample size (which is po…

stat.ME20115 cited

Inferences in Bayesian variable selection problems with large model spaces

Gonzalo Garcia-Donato, Miguel Angel Martinez-Beneito

An important aspect of Bayesian model selection is how to deal with huge model spaces, since exhaustive enumeration of all the models entertained is unfeasible and inferences have…