9 citations · 24 across the 11 of their papers we have counts for
12 papers
Media Bias and Polarization through the Lens of a Markov Switching Latent Space Network Model
Roberto Casarin, Antonio Peruzzi, Mark F. J. Steel
News outlets are now more than ever incentivized to provide their audience with slanted news, while the intrinsic homophilic nature of online social media may exacerbate polarized…
Probabilistic sequential matrix factorization
Ömer Deniz Akyildiz, Gerrit J. J. van den Burg, Theodoros Damoulas +1
We introduce the probabilistic sequential matrix factorization (PSMF) method for factorizing time-varying and non-stationary datasets consisting of high-dimensional time-series. In…
Model Averaging and its Use in Economics
Mark F. J. Steel
The method of model averaging has become an important tool to deal with model uncertainty, for example in situations where a large amount of different theories exist, as are common…
In Search of Lost (Mixing) Time: Adaptive Markov chain Monte Carlo schemes for Bayesian variable selection with very large p
Jim Griffin, Krys Latuszynski, Mark Steel
The availability of data sets with large numbers of variables is rapidly increasing. The effective application of Bayesian variable selection methods for regression with these data…
Methods and Tools for Bayesian Variable Selection and Model Averaging in Univariate Linear Regression
Anabel Forte, Gonzalo Garcia-Donato, Mark Steel
In this paper we briefly review the main methodological aspects concerned with the application of the Bayesian approach to model choice and model averaging in the context of variab…
Flexible linear mixed models with improper priors for longitudinal and survival data
F. J. Rubio, M. F. J. Steel
We propose a Bayesian approach using improper priors for hierarchical linear mixed models with flexible random effects and residual error distributions. The error distribution is m…
On choosing mixture components via non-local priors
Jairo Fúquene, Mark Steel, David Rossell
Choosing the number of mixture components remains an elusive challenge. Model selection criteria can be either overly liberal or conservative and return poorly-separated components…
Individual adaptation: an adaptive MCMC scheme for variable selection problems
Jim Griffin, Krzysztof Latuszynski, Mark Steel
The increasing size of data sets has lead to variable selection in regression becoming increasingly important. Bayesian approaches are attractive since they allow uncertainty about…
Bayesian Survival Modelling of University Outcomes
Catalina A. Vallejos, Mark F. J. Steel
The aim of this paper is to model the length of registration at university and its associated academic outcome for undergraduate students at the Pontificia Universidad Católica de…
Bayesian modelling of skewness and kurtosis with two-piece scale and shape distributions
F. J. Rubio, M. F. J. Steel
We formalise and generalise the definition of the family of univariate double two--piece distributions, obtained by using a density--based transformation of unimodal symmetric cont…
On posterior propriety for the Student- linear regression model under Jeffreys priors
Catalina A. Vallejos, Mark F. J. Steel
Regression models with fat-tailed error terms are an increasingly popular choice to obtain more robust inference to the presence of outlying observations. This article focuses on B…
Adaptive MC^3 and Gibbs algorithms for Bayesian Model Averaging in Linear Regression Models
Demetris Lamnisos, Jim E. Griffin, Mark F. J. Steel
The MC (Madigan and York, 1995) and Gibbs (George and McCulloch, 1997) samplers are the most widely implemented algorithms for Bayesian Model Averaging (BMA) in linear regressi…