  We introduce an algorithm for applying a cross-wavelet transform to analysis
of quasiperiodic variations in a time-series, and introduce significance tests
for the technique. We apply a continuous wavelet transform and the
cross-wavelet algorithm to the Pearson-Readhead VLBI survey sources using data
obtained from the University of Michigan 26-m parabloid at observing
frequencies of 14.5, 8.0, and 4.8 GHz. Thirty of the sixty-two sources were
chosen to have sufficient data for analysis, having at least 100 data points
for a given time-series. Of these thirty sources, a little more than half
exhibited evidence for quasiperiodic behavior in at least one observing
frequency, with a mean characteristic period of 2.4 yr and standard deviation
of 1.3 yr. We find that out of the thirty sources, there were about four time
scales for every ten time series, and about half of those sources showing
quasiperiodic behavior repeated the behavior in at least one other observing
frequency.
