the multiple linear regression approach typically used in near - infrared spectrometry yields equations in which any amount of reflectance at the analytical wavelengths leads to a corresponding composition value . as a result , when the sample contains a component not present in the training set , erroneous composition values can arise without any indication of error . there is described a method of detecting &# 34 ; false &# 34 ; samples by constructing a multi - dimensional form in space using reflectance values of samples in a training set at a number of wavelengths . a new sample is projected into this space and a confidence test is executed to determine whether the new sample is part of the population from which the training set was drawn . the method relies on few assumptions about the structure of the data ; therefore , deviations from assumptions do not affect the results of the confidence test .