  The need to unravel modulations hidden in noisy time series of experimental
data is a well known problem, traditionally attacked through a variety of
methods, among which a popular tool is the so called Lomb-Scargle periodogram.
Recently, for a class of problems in the solar neutrino field, it has been
proposed an alternative maximum likelihood based approach, intended to overcome
some intrinsic limitations affecting the Lomb-Scargle implementation. This work
is focused to highlight the features of the likelihood methodology, introducing
in particular an analytical approach to assess the quantitative significance of
the potential modulation signals. As an example, the proposed method is applied
to the time series of the measured values of the 8B neutrino flux released by
the Super-Kamiokande collaboration, and the results compared with those of
previous analysis performed on the same data sets. It is also examined in
detail the comparison between the Lomb-Scargle and the likelihood methods,
giving in the appendix the complete demonstration of their close relationship.
