3 citations · 4 across the 12 of their papers we have counts for
13 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.…
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…
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…
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…
Low-rank bilinear autoregressive models for three-way criminal activity tensors
Gregor Zens, Carlos Díaz, 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…
Bayesian Adaptive Tensor Smoothing for Multiway Demographic Counts
Gregor Zens
Demographic data are often collected across multiple dimensions such as time, age, subnational region, and sex. Modeling such data is challenging due to the interplay of high dimen…
Model Uncertainty in Latent Gaussian Models with Univariate Link Function
Mark F. J. Steel, Gregor Zens
We consider a class of latent Gaussian models with a univariate link function (ULLGMs). These are based on standard likelihood specifications (such as Poisson, Binomial, Bernoulli,…
Flexible Bayesian Modelling of Age-Specific Counts in Many Demographic Subpopulations
Gregor Zens
Analysing age-specific mortality, fertility, and migration patterns is a crucial task in demography with significant policy relevance. In practice, such analysis is challenging whe…
Efficient Bayesian Modeling of Binary and Categorical Data in R: The UPG Package
Gregor Zens, Sylvia Frühwirth-Schnatter, Helga Wagner
In this vignette, we introduce the UPG package for efficient Bayesian inference in probit, logit, multinomial logit and binomial logit models. UPG offers a convenient estimation fr…
Ultimate Pólya Gamma Samplers -- Efficient MCMC for possibly imbalanced binary and categorical data
Gregor Zens, Sylvia Frühwirth-Schnatter, Helga Wagner
Modeling binary and categorical data is one of the most commonly encountered tasks of applied statisticians and econometricians. While Bayesian methods in this context have been av…
A Factor-Augmented Markov Switching (FAMS) Model
Gregor Zens, Maximilian Böck
This paper investigates the role of high-dimensional information sets in the context of Markov switching models with time varying transition probabilities. Markov switching models…
Bayesian shrinkage in mixture of experts models: Identifying robust determinants of class membership
Gregor Zens
A method for implicit variable selection in mixture of experts frameworks is proposed. We introduce a prior structure where information is taken from a set of independent covariate…
Implications of macroeconomic volatility in the Euro area
Niko Hauzenberger, Maximilian Böck, Michael Pfarrhofer +2
In this paper we estimate a Bayesian vector autoregressive model with factor stochastic volatility in the error term to assess the effects of an uncertainty shock in the Euro area.…