MPR_complexity function

A function to compute the MPR-complexity

A function to compute the MPR-complexity

The function computes the MPR complexity, i.e. a generalized (global) complexity measure based on the Jenson-Shannon divergence.

MPR_complexity(opd)

Arguments

  • opd: A numeric vector that details an ordinal pattern distribution.

Returns

The normalized MPR complexity measure in the range [0, 1].

Details

Generalized complexity measures combine an information measure (i.e. entropy) with the distance of the distribution from the uniform distribution ("disequilibrium"). As a global measure, MPR-complexity is insensitive to the permutation coding scheme.

Examples

x = arima.sim(model=list(ar = 0.3), n = 10^4) opd = ordinal_pattern_distribution(x = x, ndemb = 6) MPR_complexity(opd)

References

Martin, M.T., Plastino, A. and Rosso, O.A., 2006. Generalized statistical complexity measures: Geometrical and analytical properties. Physica A: Statistical Mechanics and its Applications, 369(2), pp.439-462.

Author(s)

Sebastian Sippel

  • Maintainer: Sebastian Sippel
  • License: GPL-2
  • Last published: 2019-10-28

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