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Causality and the entropy–complexity plane: Robustness and missing ordinal patterns

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  • Rosso, Osvaldo A.
  • Carpi, Laura C.
  • Saco, Patricia M.
  • Gómez Ravetti, Martín
  • Plastino, Angelo
  • Larrondo, Hilda A.

Abstract

We deal here with the issue of determinism versus randomness in time series. One wishes to identify their relative weights in a given time series. Two different tools have been advanced in the literature to such effect, namely, (i) the “causal” entropy–complexity plane [O.A. Rosso, H.A. Larrondo, M.T. Martín, A. Plastino, M.A. Fuentes, Distinguishing noise from chaos, Phys. Rev. Lett. 99 (2007) 154102] and (ii) the estimation of the decay rate of missing ordinal patterns [J.M. Amigó, S. Zambrano, M.A.F. Sanjuán, True and false forbidden patterns in deterministic and random dynamics, Europhys. Lett. 79 (2007) 50001; L.C. Carpi, P.M. Saco, O.A. Rosso, Missing ordinal patterns in correlated noises. Physica A 389 (2010) 2020–2029]. In this work we extend the use of these techniques to address the analysis of deterministic finite time series contaminated with additive noises of different degree of correlation. The chaotic series studied here was via the logistic map (r=4) to which we added correlated noise (colored noise with f−k Power Spectrum, 0≤k≤2) of varying amplitudes. In such a fashion important insights pertaining to the deterministic component of the original time series can be gained. We find that in the entropy–complexity plane this goal can be achieved without additional computations.

Suggested Citation

  • Rosso, Osvaldo A. & Carpi, Laura C. & Saco, Patricia M. & Gómez Ravetti, Martín & Plastino, Angelo & Larrondo, Hilda A., 2012. "Causality and the entropy–complexity plane: Robustness and missing ordinal patterns," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(1), pages 42-55.
    • Handle: RePEc:eee:phsmap:v:391:y:2012:i:1:p:42-55
    DOI: 10.1016/j.physa.2011.07.030
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    References listed on IDEAS

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    1. Zunino, Luciano & Zanin, Massimiliano & Tabak, Benjamin M. & Pérez, Darío G. & Rosso, Osvaldo A., 2009. "Forbidden patterns, permutation entropy and stock market inefficiency," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 388(14), pages 2854-2864.
    2. Chstoph Bandt & Faten Shiha, 2007. "Order Patterns in Time Series," Journal of Time Series Analysis, Wiley Blackwell, vol. 28(5), pages 646-665, September.
    3. Rosso, Osvaldo A. & Craig, Hugh & Moscato, Pablo, 2009. "Shakespeare and other English Renaissance authors as characterized by Information Theory complexity quantifiers," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 388(6), pages 916-926.
    4. Zunino, Luciano & Zanin, Massimiliano & Tabak, Benjamin M. & Pérez, Darío G. & Rosso, Osvaldo A., 2010. "Complexity-entropy causality plane: A useful approach to quantify the stock market inefficiency," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(9), pages 1891-1901.
    5. Kantz, Holger & Olbrich, Eckehard, 2000. "Coarse grained dynamical entropies: Investigation of high-entropic dynamical systems," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 280(1), pages 34-48.
    6. Carpi, Laura C. & Saco, Patricia M. & Rosso, O.A., 2010. "Missing ordinal patterns in correlated noises," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(10), pages 2020-2029.
    7. Keller, K. & Sinn, M., 2005. "Ordinal analysis of time series," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 356(1), pages 114-120.
    8. Lamberti, P.W & Martin, M.T & Plastino, A & Rosso, O.A, 2004. "Intensive entropic non-triviality measure," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 334(1), pages 119-131.
    9. Saco, Patricia M. & Carpi, Laura C. & Figliola, Alejandra & Serrano, Eduardo & Rosso, Osvaldo A., 2010. "Entropy analysis of the dynamics of El Niño/Southern Oscillation during the Holocene," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(21), pages 5022-5027.
    10. De Micco, L. & González, C.M. & Larrondo, H.A. & Martin, M.T. & Plastino, A. & Rosso, O.A., 2008. "Randomizing nonlinear maps via symbolic dynamics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(14), pages 3373-3383.
    11. Martin, M.T. & Plastino, A. & Rosso, O.A., 2006. "Generalized statistical complexity measures: Geometrical and analytical properties," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 369(2), pages 439-462.
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    3. Mateos, Diego M. & Zozor, Steeve & Olivares, Felipe, 2020. "Contrasting stochasticity with chaos in a permutation Lempel–Ziv complexity — Shannon entropy plane," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 554(C).
    4. Di Vece, Marzio & Garlaschelli, Diego & Squartini, Tiziano, 2023. "Reconciling econometrics with continuous maximum-entropy network models," Chaos, Solitons & Fractals, Elsevier, vol. 166(C).
    5. Viviane M. Gomes & Joao R. B. Paiva & Marcio R. C. Reis & Gabriel A. Wainer & Wesley P. Calixto, 2019. "Mechanism for Measuring System Complexity Applying Sensitivity Analysis," Complexity, Hindawi, vol. 2019, pages 1-12, April.
    6. Olivares, Felipe & Plastino, Angelo & Rosso, Osvaldo A., 2012. "Ambiguities in Bandt–Pompe’s methodology for local entropic quantifiers," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(8), pages 2518-2526.
    7. Ji, Aiwen & Shang, Pengjian, 2019. "Analysis of financial time series through forbidden patterns," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 534(C).
    8. Montani, Fernando & Deleglise, Emilia B. & Rosso, Osvaldo A., 2014. "Efficiency characterization of a large neuronal network: A causal information approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 401(C), pages 58-70.
    9. Borges, João B. & Ramos, Heitor S. & Mini, Raquel A.F. & Rosso, Osvaldo A. & Frery, Alejandro C. & Loureiro, Antonio A.F., 2019. "Learning and distinguishing time series dynamics via ordinal patterns transition graphs," Applied Mathematics and Computation, Elsevier, vol. 362(C), pages 1-1.
    10. Redelico, Francisco O. & Traversaro, Francisco & Oyarzabal, Nicolás & Vilaboa, Ivan & Rosso, Osvaldo A., 2017. "Evaluation of the status of rotary machines by time causal Information Theory quantifiers," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 470(C), pages 321-329.
    11. Wang, Xiaoyan & Tang, Ming & Guan, Shuguang & Zou, Yong, 2023. "Quantifying time series complexity by multi-scale transition network approaches," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 622(C).
    12. Traversaro, Francisco & Redelico, Francisco O., 2018. "Characterization of autoregressive processes using entropic quantifiers," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 490(C), pages 13-23.
    13. Juan G Colonna & José R H Carvalho & Osvaldo A Rosso, 2020. "Estimating ecoacoustic activity in the Amazon rainforest through Information Theory quantifiers," PLOS ONE, Public Library of Science, vol. 15(7), pages 1-21, July.
    14. Baravalle, Roman & Rosso, Osvaldo A. & Montani, Fernando, 2018. "Discriminating imagined and non-imagined tasks in the motor cortex area: Entropy-complexity plane with a wavelet decomposition," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 511(C), pages 27-39.

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