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 .