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In order to locate the nonlinear spectral regions in spectroscopic multivariate calibration an algorithm for nonlinearity tracking analysis is developed. The nonlinear parts detected in the data are then eliminated. The results with such a treatment for both the simulated and real spectral data compared favourably with those obtained by commonly used least square regression without such a procedure.
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