A Methodology for Statistical Matching with Fuzzy Logic
Patrick Noll, Paul Alpar · 2007
The Analysis of data often requires information that is not available from a single source, but from multiple sources. Statistical matching procedures are methods that help to merge information from different sources into a single data set. Traditionally, statistical matching is done on the basis of computed distances between selected variables found in all data sets. Situations where no decision can be made in traditional statistical matching, e.g., in the case of identical distances, cause problems. We present a methodology for statistical matching with fuzzy logic which solves these problems. After a short introduction, the basics of traditional statistical matching are presented. The description of the theory of statistical fuzzy matching follows thereafter. The paper concludes with a short example.