are $\log K=-3.34\pm1.00$, $-1.75\pm0.97$ and $-2.78\pm0.76$ respectively. If adopting $\log K<-2.18$ as the criterion for rejecting a model (@Kass1995), the obtained Bayes factors imply that for the current observation data, the periodic models are not preferable [to]{} the aperiodic models.

False-alarm Probability of the Periodicity
------------------------------------------

[@Vaughan2016] showed that red-noise stochastic processes can easily produce false positive periodicity in few-cycle light curves of AGNs. The current light curve data of Ark 120 only has roughly two cycles of the period. Thus, it is important to appropriately calibrate the false alarm probability (e.g., @Koen1990 [@Barth2018; @VanderPlas2018]). False alarm probability essentially measures the probability that an aperiodic variation process (the null hypothesis) can produce spurious periodicity as strong or even stronger than that detected in the observed data. We perform null hypothesis simulations as follows. For a given aperiodic PSD model, we run `RECON` to obtain a posterior sample of model parameters, from which we randomly draw a subsample to generate a set of mock data with exactly the same sampling pattern as the observed data. To simulate the observation noises, independent Gaussian [noise with standard deviation]{} equal to the measurement errors are added into the generated [artificial]{} data. We then apply 