Semi-nonparametric approach for measured data reconciliation based on the Gram-Charlier series expansion

• Main Authors: Vladimir Garanin, Konstantin Semenov
• Format: Article
• Language: English
• Published: Elsevier 2021-12-01
• Series: Measurement: Sensors
• Subjects: Data reconciliation; Measurement error; Accuracy increase; Gram-Charlier series; Semi-nonparametric statistics
• Online Access: http://www.sciencedirect.com/science/article/pii/S2665917421003147
• ISSN: 2665-9174

This paper discusses the applicability of data reconciliation approaches in metrology and mentions the existed shortcomings. The semi-parametric method based on Gram-Charlier series expansion is presented for overcoming the obstacles preventing the wider spread of the measured data reconciliation in metrological practice. The proposed approach allows the fast estimation of potential accuracy increase that matters for adaptive measurement systems. The corresponded expressions and tests are presented.