We applied principal component analysis (PCA) to the study of five ground level enhancements (GLEs) of cosmic ray (CR) events. The nature of the multivariate data involved makes PCA a useful tool for this study. A subroutine program written and implemented in the R software environment generated interesting principal components. Analysis of the results shows that the method can distinguish between neutron monitors (NMs) that observed Forbush decreases from those that observed GLEs at the same time. The PCA equally assigned NMs with identical signal counts with the same correlation factor (r) and those with close r values equally have a close resemblance in their CR counts. The results further indicate that while NMs that have the same time of peak may not have the same r, most NMs that had the same r also had the same time of peak. Analyzing the second principal components yielded information on the differences between NMs having opposite but the same or close values of r. NMs that had the same r equally had the tendency of being close in latitude.
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