Improved selectivity in spectroscopy by multivariate calibration
- 1 October 1987
- journal article
- research article
- Published by Wiley in Journal of Chemometrics
- Vol. 1 (4) , 201-219
- https://doi.org/10.1002/cem.1180010403
Abstract
This paper illustrates some advantages of indirect multivariate calibration over conventional calibration: selectivity enhancement and outlier detection. Partial least squares (PLS) calibration is applied for quantitative analysis in the presence of interferences that would make both conventional single‐wavelength calibration and direct multicomponent analysis impossible. The PLS algorithm is illustrated graphically, and the importance of outlier detection is demonstrated.Keywords
This publication has 7 references indexed in Scilit:
- Partial least-squares regression: a tutorialAnalytica Chimica Acta, 1986
- Comparison of Linear Statistical Methods for Calibration of NIR InstrumentsJournal of the Royal Statistical Society Series C: Applied Statistics, 1986
- Multivariate Calibration When the Error Covariance Matrix Is StructuredTechnometrics, 1985
- Comparison of prediction methods for multicollinear dataCommunications in Statistics - Simulation and Computation, 1985
- Multivariate calibration. II. Chemometric methodsTrAC Trends in Analytical Chemistry, 1984
- The Collinearity Problem in Linear Regression. The Partial Least Squares (PLS) Approach to Generalized InversesSIAM Journal on Scientific and Statistical Computing, 1984
- Cross-Validatory Choice and Assessment of Statistical PredictionsJournal of the Royal Statistical Society Series B: Statistical Methodology, 1974