Dissertation on understanding and minimizing measurement error with Hidden Markov Models.

Trueness, accuracy and precision of results are very important in analytical measurements such as thermal analysis.

DTSA 5706 Measurement System Analysis Specialization: Data Science Methods for Quality Improvement Instructor: Wendy Martin, Instructor, W. Edwards Deming Professor of Management Prior knowledge ...

Technical Terms Measurement error: The discrepancy between the recorded value and the true value, arising from imperfections in measurement instruments or procedures.

Measurement error is an important problem that has not been studied very well in the context of functional data analysis. To the best of our knowledge, there are no existing methods that address the ...

Very often, in the test and measurement industry, a measurement is made by instrumentation, which is often subject to errors. It is difficult to estimate the true value of the measured quantity given ...

This article explores ways to avoid errors and make particle analysis methods more accurate and reliable.

Time-series studies are commonly used to investigate short-term health effects of ambient air-pollutant concentrations. In these studies, individual-level personal-exposure measurements are rarely ...

Most phylogenetically based statistical methods for the analysis of quantitative or continuously varying phenotypic traits assume that variation within species is absent or at least negligible, which ...

Guided by a pre-analysis plan, they produce 90 linked weather-household datasets that vary by the spatial anonymization method and the remote sensing weather product. Highlights of the article: ...