3 papers
stat.ME2026
What is your Prior Worth? Effective Sample Size and Sample Size Planning for Gaussian Graphical Models
Giuseppe Arena, Lourens Waldorp, Maarten Marsman
In Bayesian analysis, the prior effective sample size (ESS) expresses the information carried by a prior distribution in units of observations, quantifying how much independent inf…
stat.ME2026
Comparing Variable Selection and Model Averaging Methods for Logistic Regression
Nikola Sekulovski, František Bartoš, Don van den Bergh +6
Model uncertainty is a central challenge in statistical models for binary outcomes such as logistic regression, arising when it is unclear which predictors should be included in th…
stat.ME2026
Bayesian Inference for Discrete Markov Random Fields Through Coordinate Rescaling
Giuseppe Arena, Maarten Marsman
Discrete Markov random fields are undirected graphical models that capture complex conditional dependencies between discrete variables. Conducting exact posterior inference in thes…