8 papers
Marginal Data Augmentation for Efficient Bayesian Modeling of Counts and Rates with a Demographic Application
Gregor Zens, Sylvia Frühwirth-Schnatter
Count data models are ubiquitous in many fields, yet Bayesian data augmentation algorithms for such models frequently encounter challenges with Markov chain Monte Carlo efficiency.…
Low-rank bilinear autoregressive models for three-way criminal activity tensors
Gregor Zens, Carlos DÃaz, Daniele Durante +1
Criminal activity data are typically available via a three-way tensor encoding the reported frequencies of different crime categories across time and space. The challenges that ari…
Probabilistic Estimation of Hidden Migrant Fatalities Along the Central Mediterranean Route
Gregor Zens, Zoe Sigman
Estimating the number of migrants who die or go missing along dangerous routes such as the Central Mediterranean remains challenging as available records are incomplete. Some incid…
Dynamic Count Models with Flexible Innovation Processes for Irregular Maritime Migration
Gregor Zens, Jakub Bijak
Motivated by the challenge of analyzing the dynamics of weekly sea border crossings in the Mediterranean (2015-2025) and the English Channel (2018-2025), we develop a Bayesian dyna…
Bayesian Matrix Factor Models for Demographic Analysis Across Age and Time
Gregor Zens
Analyzing demographic data collected across multiple populations, time periods, and age groups is challenging due to the interplay of high dimensionality, demographic heterogeneity…
Scalable Variable Selection and Model Averaging for Latent Regression Models Using Approximate Variational Bayes
Gregor Zens, Mark F. J. Steel
We propose a fast and theoretically grounded method for Bayesian variable selection and model averaging in latent variable regression models. Our framework addresses three interrel…