Description Usage Arguments Details Value Author(s) References Examples

View source: R/complexity_measures.R

The function computes the Fisher information, i.e. a local information measure based on two different discretizations.

1 | ```
fis(opd, discretization)
``` |

`opd` |
A numeric vector that details an ordinal pattern distribution in a user-specified permutation coding scheme. |

`discretization` |
The discretization scheme to use, either 'Olivares.2012' or 'Ferri.2009' |

The Fisher information is a local information and complexity measure, computed based on the ordinal pattern distribution. The Fisher information is based on local gradients, hence it is sensitive to the permutation coding scheme. Options for discretization: 'Olivares.2012' or 'Ferri.2009', following Fisher Information discretization schemes in the respective publications.

The normalized Fisher information measure in the range [0, 1].

Sebastian Sippel

Olivares, F., Plastino, A. and Rosso, O.A., 2012. Ambiguities in Bandt-Pompe's methodology for local entropic quantifiers. Physica A: Statistical Mechanics and its Applications, 391(8), pp.2518-2526. Ferri, G.L., Pennini, F. and Plastino, A., 2009. LMC-complexity and various chaotic regimes. Physics Letters A, 373(26), pp.2210-2214.

1 2 3 | ```
x = arima.sim(model=list(ar = 0.3), n = 10^4)
opd = ordinal_pattern_distribution(x = x, ndemb = 6)
fis(opd = opd)
``` |

```
[1] 0.02480772
```

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