Statistical analysis for nuclear forensics experiments

Abstract

AbstractAs with any type of forensics, nuclear forensics seeks to infer historical information using models and data. This article connects nuclear forensics and calibration. We present statistical analyses of a calibration experiment that connect several responses to the associated set of input values and then ‘make a measurement’ using the calibration model. Previous and upcoming real experiments involving production of PuO2 powder motivate this article. Both frequentist and Bayesian approaches are considered, and we report findings from a simulation study that compares different analysis methods for different underlying responses between inputs and responses, different numbers of responses, different amounts of natural variability, and replicated or non‐replicated calibration experiments and new measurements.