Combining homogeneous groups of preclassified observations with application to international trade

This article proposes three methods for merging homogeneous clusters of observations that are grouped according to a pre‐existing (known) classification. This clusterwise regression problem is at the very least compelling in analyzing international trade data, where transaction prices can be grouped according to the corresponding origin–destination combination. A proper merging of these prices could simplify the analysis of the market without affecting the representativeness of the data and highlight commercial anomalies that may hide frauds. The three algorithms proposed are based on an itera... Mehr ...