Abstract
A new approach is proposed for the detection of changes in the instrumental response of near-infrared spectrometers over time. This approach is based on simulating possible instrumental differences and performing a principal component analysis of the simulated data set. This multivariate approach is tested on a real near-infrared data set and the results are compared to those obtained by the several univariate diagnostic procedures commonly used to check the stability of the response of a nearinfrared spectrometer over time. Advantages and drawbacks of this new approach are discussed. A simulated data set is used to study the influence of using different types of standards on the results obtained by this approach.
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