Correlation in the application of the triple-to-double coincidence ratio method with unequal photomultiplier tube efficiencies

Abstract

Counting data from the triple-to-double coincidence ratio (TDCR) method are by their nature highly correlated. In the general case of unequal phototube detection efficiencies, the highly correlated nature of the data combined with the need to apply methods to solve a system of equations makes proper uncertainty analysis difficult. Removing the correlations from the data prior to analysis may assist in this endeavor. This paper describes the de-correlation of TDCR data by the application of a particular linear transform, the Mahalanobis transform. A programming example in MATLAB is given and a practical example of the use of this technique in the analysis of TDCR data is presented.