Periodic Radio Variability of Unevenly Sampled Time Series: Weighted Wavelet Z-Transform Analysis

The observation of period radio variability in astronomical systems provides astronomers with valuable information on the physical nature of the system. However, because of poor weather conditions and complex underlying astrophysical processes, the data sets of astronomical fields always feature sparse and unevenly spaced sampling. In this paper, a search for periodicity has been presented using the Weighted Wavelet Z-transform (WWZ) technique of the radio light curves of the high mass X-ray binary EXO 2030+375, the weighted wavelet Z-transform (WWZ) technique which is based on the principle of wavelet analysis can detect the characteristic parameter of the time series which the data is unevenly spaced. Periodicity analysis using two other transform methods, Lomb-Scargle periodogram (LS) and Phase Disoersion Minimization (PDM), served for verification and comparison, the results from the three methods are in excellent agreement and identify one persistent periods of ~0.3 (7 hours) day, it provides a reasonable method for characteristic parameter extraction of unevenly spaced time series.