Evaluating Uncertainty of Microwave Calibration Models With Regression Residuals

被引：0
|
作者：
Williams, Dylan F. [1 ]
Jamroz, Benjamin F. [1 ]
Rezac, Jacob D. [1 ]
Jones, Robert D. [1 ]
机构：
[1] NIST, Boulder, CO 80305 USA
来源：
IEEE TRANSACTIONS ON MICROWAVE THEORY AND TECHNIQUES | 2020年 / 68卷 / 06期
关键词：
Calibration; Uncertainty; Microwave measurement; Microwave theory and techniques; Measurement uncertainty; Biological system modeling; Monte Carlo methods; Coupling corrections; microwave calibration; on-wafer measurement; uncertainty; SIMULTANEOUS CONFIDENCE BANDS; BOOTSTRAP METHODS; JACKKNIFE;
D O I：
10.1109/TMTT.2020.2983358
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
We present the sensitivity-analysis and Monte Carlo algorithms 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 that we evaluate can be used to estimate the total uncertainty of a calibrated measurement when combined with the prediction intervals for that measurement.
引用
收藏
页码：2454 / 2467
页数：14
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