Splitting of calibration data by cluster analysis

The topic of the present paper is the splitting of calibration data into subgroups with improved linearity in each group. The method proposed is based on a criterion which is a weighted average of a Mahalanobis distance and a squared regression residual. The algorithm used to find the solution is based on fuzzy clustering. Two examples are given to illustrate the theory.