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

For years, a core set of satellite measurements has shaped how scientists, policymakers and modelers understand the Arctic’s ...

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, ...

This file type includes high resolution graphics and schematics when applicable. Monitoring the current consumed in electronic systems has become critical as more functionality packs into tighter ...

The increasing number of power domains found in power management ICs (PMICs) targeted for portable applications places heavy demands on the few precision DC resources found in many ATE systems. Even ...