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.

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8194252PMC
http://dx.doi.org/10.1109/tmtt.2020.2983358DOI Listing

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