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07/13/2023
Dynamic Mixture of Finite Mixtures of Factor Analysers with Automatic Inference on the Number of Clusters and Factors
Mixtures of factor analysers (MFA) models represent a popular tool for f...
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03/01/2023
Generalized Cumulative Shrinkage Process Priors with Applications to Sparse Bayesian Factor Analysis
The paper discusses shrinkage priors which impose increasing shrinkage i...
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01/16/2023
When it counts – Econometric identification of the basic factor model based on GLT structures
Despite the popularity of factor models with sparse loading matrices, li...
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12/05/2022
Bayesian Reconciliation of Return Predictability
This article considers a stable vector autoregressive (VAR) model and in...
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11/01/2022
Cover It Up! Bipartite Graphs Uncover Identifiability in Sparse Factor Analysis
Despite the popularity of factor models with sparse loading matrices, li...
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07/25/2022
Sparse Bayesian State-Space and Time-Varying Parameter Models
In this chapter, we review variance selection for time-varying parameter...
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03/01/2021
Factor-augmented Bayesian treatment effects models for panel outcomes
We propose a new, flexible model for inference of the effect of a binary...
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01/29/2021
How many data clusters are in the Galaxy data set? Bayesian cluster analysis in action
In model-based clustering, the Galaxy data set is often used as a benchm...
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01/07/2021
Efficient Bayesian Modeling of Binary and Categorical Data in R: The UPG Package
We introduce the UPG package for highly efficient Bayesian inference in ...
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12/22/2020
Spying on the prior of the number of data clusters and the partition distribution in Bayesian cluster analysis
Mixture models represent the key modelling approach for Bayesian cluster...
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11/13/2020
Ultimate Pólya Gamma Samplers – Efficient MCMC for possibly imbalanced binary and categorical data
Modeling binary and categorical data is one of the most commonly encount...
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05/20/2020
Dynamic mixtures of finite mixtures and telescoping sampling
Within a Bayesian framework, a comprehensive investigation of the model ...
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12/06/2019
Triple the gamma – A unifying shrinkage prior for variance and variable selection in sparse state space and TVP models
Time-varying parameter (TVP) models are very flexible in capturing gradu...
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07/16/2019
Shrinkage in the Time-Varying Parameter Model Framework Using the R Package shrinkTVP
Time-varying parameter (TVP) models are widely used in time series analy...
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06/21/2018
