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<H1><A NAME="SECTION00020000000000000000">Detecting weak nonlinearity</A></H1>
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Many quantities have been discussed in the literature that can be used to
characterise nonlinear time series. For the purpose of nonlinearity testing we
need such quantities that are particular powerful in discriminating linear
dynamics and weakly nonlinear signatures -- strong nonlinearity is usually
more easily detectable. An important objective criterion that can be used to
guide the preferred choice is the discrimination <EM>power</EM> of the resulting
test. It is defined as the probability that the null hypothesis is rejected
when it is indeed false.  It will obviously depend on how and how strongly the
data actually deviates from the null hypothesis.
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<I>Thomas Schreiber <BR>
Mon Aug 30 17:31:48 CEST 1999</I>
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