3 papers
stat.ML2026
Conformalized Regression for Continuous Bounded Outcomes
Zhanli Wu, Fabrizio Leisen, F. Javier Rubio
Regression problems with bounded continuous outcomes frequently arise in statistical and machine learning applications, such as the analysis of rates and proportions. A central cha…
stat.CO2026
Bayesian variable selection in sample selection models using spike-and-slab priors
Adam J. Iqbal, Emmanuel O. Ogundimu, F. Javier Rubio
Sample selection models are a widely used approach for correcting bias caused by data that are missing not at random. Their formulation requires specifying the variables that influ…
stat.ME2026
Bayesian variable and hazard structure selection in the General Hazard model
Yulong Chen, Jim Griffin, Francisco Javier Rubio
The proportional hazards (PH) and accelerated failure time (AFT) models are the most widely used hazard structures for analysing time-to-event data. When the goal is to identify va…