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

In large epidemiological studies, it is often impractical to collect direct quantitative measures of exposure on all subjects. Cohort studies of the effects of traffic-related air pollution are ...

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 ...

This paper presents an EM algorithm for semiparametric likelihood analysis of linear, generalized linear, and nonlinear regression models with measurement errors in explanatory variables. A structural ...

Ensuring parts meet specification is crucial and so it helps to have confidence in your measurement system. Parts that don’t meet specification, whether gauging composition or measuring thickness, ...