  We applied principal component analysis (PCA) to the study of five ground
level enhancement (GLE) 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 R software environment generated interesting
principal components. Analysis of the results shows that the method can
distinguish between neutron monitors (NMs) that observed Forbush decrease (FD)
from those that observed GLE 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 in close latitude.
