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Based on a 20-year-long multiband observation of its light-curve, it wasconjectured that the quasar SDSSJ025214.67-002813.7 has a periodicity of ~4.4years. These observations were acquired at a highly irregular sampling rate andfeature long intervals of missing data. In this setting, the inference over thelight-curve's spectral content requires, in addition to classic Fouriermethods, a proper model of the probability distribution of the missingobservations. In this article, we address the detection of the periodicity of alight-curve from partial and irregularly-sampled observations using Gaussianprocesses, a Bayesian nonparametric model for time series. This methodologyallows us to evaluate the veracity of the claimed periodicity of theabovementioned quasar and also to estimate its power spectral density. Our maincontribution is the confirmation that considering periodic component definitelyimproves the modeling of the data, although being the source originallyselected by a large sample of objects, the possibility that this is a chanceresult cannot be ruled out.

Detecting the periodicity of highly irregularly sampled light-curves with Gaussian processes: the case of SDSSJ025214.67-002813.7