Gregor Zens
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View article: Scalable Variable Selection and Model Averaging for Latent Regression Models Using Approximate Variational Bayes
Scalable Variable Selection and Model Averaging for Latent Regression Models Using Approximate Variational Bayes Open
We propose a fast and theoretically grounded method for Bayesian variable selection and model averaging in latent variable regression models. Our framework addresses three interrelated challenges: (i) intractable marginal likelihoods, (ii)…
View article: Flexible Bayesian modelling of age-specific counts in many demographic subpopulations
Flexible Bayesian modelling of age-specific counts in many demographic subpopulations Open
Analysing age-specific mortality, fertility, and migration patterns is a crucial task in demography with significant policy relevance. In practice, such analysis is challenging when studying a large number of subpopulations, due to small o…
View article: Low-rank bilinear autoregressive models for three-way criminal activity tensors
Low-rank bilinear autoregressive models for three-way criminal activity tensors Open
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 arise in the design of interpretable, yet realistic, model-bas…
View article: Subnational variations in the quality of household survey data in sub-Saharan Africa
Subnational variations in the quality of household survey data in sub-Saharan Africa Open
Nationally representative household surveys collect geocoded data that are vital to tackling health and other development challenges in sub-Saharan Africa. Scholars and practitioners generally assume uniform data quality but subnational va…
View article: Bayesian Matrix Factor Models for Demographic Analysis Across Age and Time
Bayesian Matrix Factor Models for Demographic Analysis Across Age and Time Open
Analyzing demographic data collected across multiple populations, time periods, and age groups is challenging due to the interplay of high dimensionality, demographic heterogeneity among groups, and stochastic variability within smaller gr…
View article: Model Uncertainty in Latent Gaussian Models with Univariate Link Function
Model Uncertainty in Latent Gaussian Models with Univariate Link Function Open
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, Erlang, etc.), but incorporate a latent normal linear regr…
View article: Interrelated drivers of migration intentions in Africa: Evidence from Afrobarometer surveys
Interrelated drivers of migration intentions in Africa: Evidence from Afrobarometer surveys Open
Migration is influenced by various factors, including economic, political, social, and environmental drivers. While the multicausal nature of migration has been recognized, there are considerable gaps in understanding how different drivers…
View article: Model Uncertainty in Latent Gaussian Models with Univariate Link Function
Model Uncertainty in Latent Gaussian Models with Univariate Link Function Open
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, Erlang, etc.) but incorporate a latent normal linear regre…
View article: Flexible Bayesian Modelling of Age-Specific Counts in Many Demographic Subpopulations
Flexible Bayesian Modelling of Age-Specific Counts in Many Demographic Subpopulations Open
Analysing age-specific mortality, fertility, and migration patterns is a crucial task in demography with significant policy relevance. In practice, such analysis is challenging when studying a large number of subpopulations, due to small o…
View article: Ultimate Pólya Gamma Samplers–Efficient MCMC for Possibly Imbalanced Binary and Categorical Data
Ultimate Pólya Gamma Samplers–Efficient MCMC for Possibly Imbalanced Binary and Categorical Data Open
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 available for decades now, they often require a high level of…
View article: Ultimate Pólya Gamma Samplers–Efficient MCMC for Possibly Imbalanced Binary and Categorical Data
Ultimate Pólya Gamma Samplers–Efficient MCMC for Possibly Imbalanced Binary and Categorical Data Open
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 available for decades now, they often require a high level of…
View article: Ultimate Pólya Gamma Samplers – Efficient MCMC for possibly imbalanced binary and categorical data
Ultimate Pólya Gamma Samplers – Efficient MCMC for possibly imbalanced binary and categorical data Open
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 available for decades now, they often require a high level of…
View article: Efficient Bayesian Modeling of Binary and Categorical Data in R: The UPG Package
Efficient Bayesian Modeling of Binary and Categorical Data in R: The UPG Package Open
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 framework for balanced and imbalanced data settings where sam…
View article: Efficient Bayesian Modeling of Binary and Categorical Data in R: The UPG\n Package
Efficient Bayesian Modeling of Binary and Categorical Data in R: The UPG\n Package Open
In this vignette, we introduce the UPG package for efficient Bayesian\ninference in probit, logit, multinomial logit and binomial logit models. UPG\noffers a convenient estimation framework for balanced and imbalanced data\nsettings where …
View article: Ultimate Pólya Gamma Samplers -- Efficient MCMC for possibly imbalanced binary and categorical data
Ultimate Pólya Gamma Samplers -- Efficient MCMC for possibly imbalanced binary and categorical data Open
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 available for decades now, they often require a high level of…
View article: Tax Preferences, Partisanship and Perceptions of Society:Evidence from Austria
Tax Preferences, Partisanship and Perceptions of Society:Evidence from Austria Open
This article systematically investigates the attitudes of voters towards capital taxation and further topics in the realm of the welfare state. We revisit various streams of literature and explore which views, beliefs and perceptions are c…
View article: A Factor-Augmented Markov Switching (FAMS) Model
A Factor-Augmented Markov Switching (FAMS) Model Open
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 are commonly employed in empirical macroeconomic research a…
View article: Bayesian shrinkage in mixture-of-experts models: identifying robust determinants of class membership
Bayesian shrinkage in mixture-of-experts models: identifying robust determinants of class membership Open
A method for implicit variable selection in mixture-of-experts frameworks is proposed.
\nWe introduce a prior structure where information is taken from a set of independent
\ncovariates. Robust class membership predictors are identified us…
View article: Bayesian shrinkage in mixture of experts models: Identifying robust\n determinants of class membership
Bayesian shrinkage in mixture of experts models: Identifying robust\n determinants of class membership Open
A method for implicit variable selection in mixture of experts frameworks is\nproposed. We introduce a prior structure where information is taken from a set\nof independent covariates. Robust class membership predictors are identified\nusi…
View article: Bayesian shrinkage in mixture of experts models: Identifying robust determinants of class membership
Bayesian shrinkage in mixture of experts models: Identifying robust determinants of class membership Open
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 covariates. Robust class membership predictors are identified using …
View article: Does the environment matter for poverty reduction ? the role of soil fertility and vegetation vigor in poverty reduction
Does the environment matter for poverty reduction ? the role of soil fertility and vegetation vigor in poverty reduction Open
The debate on the environment-poverty
\n nexus is inconclusive, with past research unable to identify
\n the causal dynamics. This paper uses a unique global panel
\n data set that links (survey and census derived) poverty data
\n to measu…