  We perform an independent search for sinusoidal-based modulation in the
recently released ANAIS-112 data, which could be induced by dark matter
scatterings. We then evaluate this hypothesis against the null hypothesis that
the data contains only background, using four different model comparison
techniques. These include frequentist, Bayesian, and two information
theory-based criteria (AIC and BIC). This analysis was done on both the
residual data (by subtracting the exponential fit obtained from the ANAIS-112
Collaboration) as well as the total (non-background subtracted) data. We find
that according to the Bayesian model comparison test, the null hypothesis of no
modulation is decisively favored over a cosine-based annual modulation for the
non-background subtracted dataset in 2-6 keV energy range. None of the other
model comparison tests decisively favor any one hypothesis over another. This
is the first application of Bayesian and information theory techniques to test
the annual modulation hypothesis in ANAIS-112 data, extending our previous work
on the DAMA/LIBRA and COSINE-100 data. Our analysis codes have also been made
publicly available.
