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Implementation of Errors-in-Variables Regression and Monte Carlo Uncertainty Evaluation into Force Calibration Reporting at NIST

Published

Author(s)

Thomas W. Bartel

Abstract

The National Institute of Standards and Technology (NIST) is commencing the implementation of certain statistical procedures, namely errors-in-variables regression and Monte Carlo uncertainty evaluation, into the data analysis and reporting for the force calibration service provided by the NIST Physical Measurement Laboratory (PML). This document is intended to serve as an overview of these procedures to the users of NIST’s force calibration service, by presenting computational details of the analyses and introducing the corresponding format for the force calibration report.
Citation
Technical Note (NIST TN) - 1942
Report Number
1942

Keywords

Errors-in-variables, Monte Carlo method, Force calibration, Ordinary least squares, Regression computation, Uncertainty assessment, Uncertainty bands

Citation

Bartel, T. (2016), Implementation of Errors-in-Variables Regression and Monte Carlo Uncertainty Evaluation into Force Calibration Reporting at NIST, Technical Note (NIST TN), National Institute of Standards and Technology, Gaithersburg, MD, [online], https://doi.org/10.6028/NIST.TN.1942 (Accessed April 12, 2024)
Created November 21, 2016, Updated November 10, 2018