  New time-series analysis tools are needed in disciplines as diverse as
astronomy, economics and meteorology. In particular, the increasing rate of
data collection at multiple wavelengths requires new approaches able to handle
these data. The panchromatic correlated indices $K^{(s)}_{(fi)}$ and
$L^{(s)}_{(pfc)}$ are adapted to quantify the smoothness of a phased
light-curve resulting in new period-finding methods applicable to single- and
multi-band data. Simulations and observational data are used to test our
approach. The results were used to establish an analytical equation for the
amplitude of the noise in the periodogram for different false alarm probability
values, to determine the dependency on the signal-to-noise ratio, and to
calculate the yield-rate for the different methods. The proposed method has
similar efficiency to that found for the String Length period method. The
effectiveness of the panchromatic and flux independent period finding methods
in single waveband as well as multiple-wavebands that share a fundamental
frequency is also demonstrated in real and simulated data.
