Detecting and diagnosing prior and likelihood sensitivity with power-scaling
Detecting and diagnosing prior and likelihood sensitivity with power-scaling
Abstract Determining the sensitivity of the posterior to perturbations of the prior and likelihood is an important part of the Bayesian workflow. We introduce a practical and computationally efficient sensitivity analysis approach using importance sampling to estimate properties of posteriors resulting from power-scaling the prior or likelihood. On this basis, …