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This program is similar to MLDK2MCE, but uses distances obtained from
independent time series generated for every embedding dimension and
every Monte Carlo trial.
A time series is generated, stored in memory and checked for (exact) periodicity.
There are some values for (e.g. for the logistic map)
for which the solution becomes constant. In such a case, the initial
condition is not attracted to the one we are interested in!
Therefore, the time series will be discarded when the last iterate equals any
of the previous ones.
The values of the time series are transformed so that the maximum
possible distance will equal 1 (so the reference distance will depend
on the realization thereby introducing small additional fluctuations
in the entropy estimates);
distances are calculated using the supremum
norm.
The indices for the vectors (2.6) are randomly chosen
with or without replacing. For the former case, see MLDK2;
for the latter case, first all indices are
given a random permutation (scrambled).

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