2 papers
stat.ME2025
Valid and efficient possibilistic structure learning in Gaussian linear regression
Ryan Martin, Naomi Singer, Jonathan Williams
A crucial step in fitting a regression model to data is determining the model's structure, i.e., the subset of explanatory variables to be included. However, the uncertainty in thi…
math.ST2025
Possibilistic inferential models: a review
Ryan Martin
An inferential model (IM) is a model describing the construction of provably reliable, data-driven uncertainty quantification and inference about relevant unknowns. IMs and Fisher'…