  This paper is devoted to testing time series that exhibit behavior related to
two or more regimes with different statistical properties. Motivation of our
study are two real data sets from plasma physics with observable two-regimes
structure. In this paper we develop estimation procedure for critical point of
division the structure change of a time series. Moreover we propose three tests
for recognition such specific behavior. The presented methodology is based on
the empirical second moment and its main advantage is lack of the distribution
assumption. Moreover, the examined statistical properties we express in the
language of empirical quantiles of the squared data therefore the methodology
is an extension of the approach known from the literature. The theoretical
results we confirm by simulations and analysis of real data of turbulent
laboratory plasma.
