fis: A (low-level) function to compute the Fisher-information

In statcomp: Statistical Complexity and Information Measures for Time Series Analysis

Description

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

Usage

fis(opd, discretization)

Arguments

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'

Details

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.

Value

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

Author(s)

Sebastian Sippel

References

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.

Examples

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

Example output

[1] 0.02480772

statcomp documentation built on Oct. 18, 2019, 3:01 p.m.