Similarity index: a rapid classification method for multivariate data arrays

摘要

Provided herein is a method of determining the similarity between a first multivariate data set and a second multivariate data set. The method may be applied to rapidly assess the similarity between fluorescence spectroscopy multivariate data sets in quality control analysis. The method includes representing the data of a first and a second multivariate data set in matrix form to yield a multivariate data matrix and calculating the magnitude of an additive and subtractive combination of each multivariate data matrix. The concept of a penalty parameter is introduced to set a detectable limit of variance between the first multivariate data set and the second multivariate data set and the penalty parameter is used in combination with the magnitude of an additive and subtractive combination of each multivariate data matrix to determine a similarity value.