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The method here presented intends to minimize the effect of the gaps in thepower spectra by gap-filling preserving the original information, that is, inthe case of asteroseismology, the stellar oscillation frequency content. Wemake use of a forward-backward predictor based on autoregressive moving averagemodelling (ARMA) in the time domain. The method MIARMA is particularly suitablefor replacing invalid data such as those present in the light curves of theCoRoT satellite due to the pass through the South Atlantic Anomaly, andeventually for the data gathered by the NASA planet hunter Kepler. We select asample of stars from the ultra-precise photometry collected by theasteroseismic camera on board the CoRoT satellite: the {\delta} Scuti star HD174966, showing periodic variations of the same order as the CoRoTobservational window, the Be star HD 51193, showing longer time variations, andthe solar-like HD 49933, with rapid time variations. We showed that in somecases linear interpolations are less reliable to what was believed. Inparticular: the power spectrum of HD 174966 is clearly aliased when thisinterpolation is used for filling the gaps; the light curve of HD 51193presents a much more aliased spectrum than expected for a low frequencyharmonic signal; and finally, although the linear interpolation does not affectnoticeably the power spectrum of the CoRoT light curve of the solar-like starHD 49933, the ARMA interpolation showed rapid variations previouslyunidentified that ARMA interprets as a signal. In any case, the ARMAinterpolation method provides a cleaner power spectrum, that is, lesscontaminated by spurious frequencies. In conclusion, MIARMA appears to be asuitable method for filling gaps in the light curves of pulsating starsobserved by CoRoT since the method preserves their frequency content, which isa necessary condition for asteroseismic studies.

MIARMA: An information preserving method for filling gaps in time series. Application to CoRoT light curves