This was motivated by Steve McIntyre’s observation… “We [Steve
McIntyre and Ross McKitrick] also observed that they[Michael E.
Mann, Raymond S. Bradley and Malcolm K. Hughes] had modified the
principal components calculation so that it intentionally or
unintentionally mined for hockey stick shaped series. It was so
powerful in this respect that I could even produce a HS from
random red noise.” The basic idea of principal component
analysis (PCA) PCA is used to determine the minimum number of
factors that explain the maximum variance in multiple data sets.
In the case of the hockey stick each data set represents a
chronological set of measurements, usually a tree ring
chronology. These chronologies may vary over time in similar
ways, and in theory these variations are governed by common
factors. The single factor that explains the greatest amount of
variance is the 1st principal component. The factor that
explains the next greatest amount of variance is the second
principal component. etc. In the case of the h