The main features of the Calibration Curve Computing (CCC) Software, a tool for regression analysis developed at the INRIM, the Italian National Metrology Institute, are described in this paper. The first release of the software tool, version 1.3, has been available on the INRIM website for free download since 2015. It was developed under a Matlab environment and distributed as an executable file. The software tool featured a friendly graphical user interface, to encourage even non-Matlab users to use it. The software is able to perform regression fitting according to ordinary,weighted and weighted total least square models and it can be applied to datasets that can be characterized by uncertainties and covariances in both the dependent and the independent variable. The curves that can be fitted to the data are fractional polynomials with positive and negative exponents up to the fifth order. Recently, version 2.0 of the CCC Software has been developed and tested and will be uploaded early in 2020. The main improvements of this new version, concerning the graphical aspects and the calculation functionalities, are here described in detail, with a major focus on the enhancements obtained in the estimated accuracy of the weighted total least square regression. Validation results and the application to a real case study are also shown. The present paper is a significant expansion of a relevant abstract presented at the 'Mathematical and Statistical Methods for Metrology' Workshop, Torino, Italy, 30-31 May 2019 (Lecuna et al 2019 Mathematical and Statistical Methods for Metrology).
Calibration curve computing (CCC) software v2.0: A new release of the INRIM regression tool / Lecuna, Maricarmen; Pennecchi, F.; Malengo, A.; Spazzini, P. G.. - In: MEASUREMENT SCIENCE & TECHNOLOGY. - ISSN 0957-0233. - 31:11(2020), p. 114004. [10.1088/1361-6501/ab7d6e]
Calibration curve computing (CCC) software v2.0: A new release of the INRIM regression tool
Lecuna Maricarmen;Pennecchi F.;
2020
Abstract
The main features of the Calibration Curve Computing (CCC) Software, a tool for regression analysis developed at the INRIM, the Italian National Metrology Institute, are described in this paper. The first release of the software tool, version 1.3, has been available on the INRIM website for free download since 2015. It was developed under a Matlab environment and distributed as an executable file. The software tool featured a friendly graphical user interface, to encourage even non-Matlab users to use it. The software is able to perform regression fitting according to ordinary,weighted and weighted total least square models and it can be applied to datasets that can be characterized by uncertainties and covariances in both the dependent and the independent variable. The curves that can be fitted to the data are fractional polynomials with positive and negative exponents up to the fifth order. Recently, version 2.0 of the CCC Software has been developed and tested and will be uploaded early in 2020. The main improvements of this new version, concerning the graphical aspects and the calculation functionalities, are here described in detail, with a major focus on the enhancements obtained in the estimated accuracy of the weighted total least square regression. Validation results and the application to a real case study are also shown. The present paper is a significant expansion of a relevant abstract presented at the 'Mathematical and Statistical Methods for Metrology' Workshop, Torino, Italy, 30-31 May 2019 (Lecuna et al 2019 Mathematical and Statistical Methods for Metrology).File | Dimensione | Formato | |
---|---|---|---|
Lecuna_2020_Meas._Sci._Technol._31_114004.pdf
accesso riservato
Tipologia:
2a Post-print versione editoriale / Version of Record
Licenza:
Non Pubblico - Accesso privato/ristretto
Dimensione
691.48 kB
Formato
Adobe PDF
|
691.48 kB | Adobe PDF | Visualizza/Apri Richiedi una copia |
Pubblicazioni consigliate
I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
https://hdl.handle.net/11583/2882325