Abstract
Classical, inverse and conditional multivariate calibration techniques
are studied using application data obtained from experiments and artificial data for the case in which the independent variable is fixed. The
aim is to obtain the best model for the prediction of the independent
variable(s) and the confidence regions of this prediction. In addition,
the outliers in the observed data and in the predicted data set are also
examined in this study.