Evaluating Uncertainty of Microwave Calibrations with Regression Residuals
Dylan F. Williams, Benjamin F. Jamroz, Jake D. Rezac, Robert D. Jones
We present a sensitivity-analysis and a Monte-Carlo algorithm for evaluating the uncertainty of multivariate microwave calibration models with regression residuals. We then use synthetic data to verify the performance of the algorithms and explore their limitations in the presence of correlated errors. The uncertainties we evaluate can be used to estimate the total uncertainty of a calibrated measurement when combined with the prediction intervals for that measurement.
IEEE Transactions on Microwave Theory and Techniques
, Jamroz, B.
, Rezac, J.
and Jones, R.
Evaluating Uncertainty of Microwave Calibrations with Regression Residuals, IEEE Transactions on Microwave Theory and Techniques, [online], https://doi.org/10.1109/TMTT.2020.2983358
(Accessed May 17, 2022)