Bayesian uncertainty analysis represents a powerful statistical framework that integrates prior knowledge with observed measurement data to quantify uncertainty in a consistent probabilistic manner.

Assess a discrete measurement. Perform analyzes for potential and long term control and capability. Make decisions on measurement systems process improvement. In this module, we will learn to identify ...

Yang, Mochen, Edward McFowland III, Gordon Burtch, and Gediminas Adomavicius. "Achieving Reliable Causal Inference with Data-Mined Variables: A Random Forest Approach ...

Linear multiregression dynamic models, which combine a graphical representation of a multivariate time series with a state space model, have been shown to be a promising class of models for ...