Dear time-series specialist:
I've got some time series representing measurements from a physical
process, like atomic decay data. These time series look almost
random, but should hopefully be distinguishable as they were taken
under different conditions.
I am looking for statistical approaches that are sensitive enough to
discriminate between such series of measurements. Preferably, there
are also implementations in R.
Please note that I am not interested in tests of random number
generators, but on tests that can discriminate time series based on
statistical (or mining) features. Simple summary tests do not work,
also some of the simpler non-linear tests failed.
Thanks, Hans Werner
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