Skip to content
Archive of posts tagged identifiable

Convergence Monitoring for Non-Identifiable and Non-Parametric Models

Becky Passonneau and colleagues at the Center for Computational Learning Systems (CCLS) at Columbia have been working on a project for ConEd (New York’s major electric utility) to rank structures based on vulnerability to secondary events (e.g., transformer explosions, cable meltdowns, electrical fires). They’ve been using the R implementation BayesTree of Chipman, George and McCulloch’s […]