The Jurkevich method is based on the expected mean square deviation
and it is less inclined to
generate spurious periodicities than Fourier analysis. It tests a
run of trial periods around
which the data are folded. All data are assigned to m group according
to their phases around each
trial period and the variance Vi2 for each group, and the sums Vm2
of all groups are computed.
For a trial period equal to the true one, Vm2 reaches its minimum, and
a "good" period will give a
much reduced variance relative to those given by other false trial
periods and with almost
constant values. Kidger et al. (1992) introduced a fraction of the
variance
where Vm2 is the normalized value. In the normalized plot, a
value of Vm2 = 1 means f = 0 and
hence there is no periodicity at all. The best periods can be
identified from the plot: a value
of 
suggests there is a very strong periodicity and a
value of f < 0.25 suggests that the
periodicity, if genuine, is a weak one.