and $\beta$ are set to be uniform over a range (1, 5) and ($-3$, 5) respectively.

Table \[tab\_par\] summarizes the inferred parameter values for the above three PSD models. The MCMC algorithm adopted in the calculations can not calculate the uncertainty of the obtained Bayesian evidence in a single running. We [ran]{} the algorithm 10 times and set the best estimate of the evidence [based on]{} the mean and the associated uncertainty [based on]{} the standard deviation. The Bayes factor of the DRW and BPL models relative to the SPL model are $\log K=-2.37\pm1.00$ and $0.31\pm0.82$ respectively. This indicates that all the three PSD models give similarly good fits to the observed data.

![image](lsp.pdf){width="100.00000%"}

Periodicity Analysis and False-Alarm Probability
================================================

As described above, visual inspection reveals an interval of 20 years between peaks/troughs, potentially implying that there exists a $\sim20$-year periodicity in the light curve. Below we employ several methods to [attempt to confirm]{} the periodicity and estimate the associated false-alarm probability.

Periodicity {#sec_per}
-----------

We use three methods to [identify possible]{} periodicity in the light curve as follows.

-   [*Lomb-Scargle (LS) periodogram*]{}[^4]. The top right panel of Figure \[fig\_period\] shows the LS periodogram of the merged light curve, which 