ASTM E2617 - 17

Standard Practice for Validation of Empirically Derived Multivariate Calibrations

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1.1 This practice covers requirements for the validation of empirically derived calibrations (Note 1) such as calibrations derived by Multiple Linear Regression (MLR), Principal Component Regression (PCR), Partial Least Squares (PLS), Artificial Neural Networks (ANN), or any other empirical calibration technique whereby a relationship is postulated between a set of variables measured for a given sample under test and one or more physical, chemical, quality, or membership properties applicable to that sample.Note 1: Empirically derived calibrations are sometimes referred to as “models” or “calibrations.” In the following text, for conciseness, the term “calibration” may be used instead of the full name of the procedure.1.2 This practice does not cover procedures for establishing said postulated relationship.1.3 This practice serves as an overview of techniques used to verify the applicability of an empirically derived multivariate calibration to the measurement of a sample under test

Number of pages: 11

International relationships:

ICS: 17.020 - Metrology and measurement in general

Item number: A001250