ISSN 0869-6632 (Print)
ISSN 2542-1905 (Online)


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Sysoeva M. V., Dikanev T. V., Sysoev I. V. Selecting time scales for empirical model construction. Izvestiya VUZ. Applied Nonlinear Dynamics, 2012, vol. 20, iss. 2, pp. 54-62. DOI: 10.18500/0869-6632-2012-20-2-54-62

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Russian
Article type: 
Article
UDC: 
530.182, 51-73

Selecting time scales for empirical model construction

Autors: 
Sysoeva Marina Vyacheslavovna, Yuri Gagarin State Technical University of Saratov
Dikanev Taras Viktorovich, Huawei Technologies Co in Russia
Sysoev Ilya V., Saratov State University
Abstract: 

The task is considered of taking into account the multiple time scales of original time series, with these time series being used for Granger causality estimation. It is proposed to use the combination of prediction length and lag, different in value, that could be fruitful for comparatively short times series, e. g. of medical-biological nature. The automated methods are constructed to select lag and prediction length values. The proposed approach is tested on a set of examples – ethalon systems. Based on this consideration the concrete proposal for prediction length value is formulated.

Reference: 
  1. Granger CWJ. Investigating causal relations by econometric models and cross-spectral methods. Econometrica. 1969;37(3):424–438.
  2. Gourevitch B, Bouquin-Jeannes RL, Faucon G. Linear and nonlinear causality between signals: methods, examples and neurophysiological applications. Biological Cybernetics. 2006;95(4):349–369. DOI: 10.1007/s00422-006-0098-0.
  3. Rosenblum MG, Pikovsky AS. Detecting direction of coupling in interacting oscillators. Physical Review E. 2001;64:045202. DOI: 10.1103/PhysRevE.64.045202.
  4. Abhyankar A. Linear and nonlinear Granger causality: Evidance from the U.K. stock index futures markets. The Journal of Futures Markets. 1998;18(5):519–540.
  5. Bernasconi C, Konig P. On the directionality of cortical interactions studied by structural analysis of electrophysiological recordings. Biol. Cybern. 1999;81:199–210. DOI: 10.1007/s004220050556.
  6. Smirnov DА, Barnikol UB, Barnikol TT, Bezruchko BP, Hauptmann C, Buehrle C, Maarouf M, Sturm V, Freund HJ, Tass PA. The generation of Parkinsonian tremor as revealed by directional coupling analysis. Europhysics Letters. 2008;83(2):20003. DOI: 10.1209/0295-5075/83/20003.
  7. Sysoev IV, Karavaev AS, Nakonechnyj PI. Role of model nonlinearity for granger causality based coupling estimation for pathological tremor. Izvestiya VUZ. Applied Nonlinear Dynamics. 2010;18(4):81–90 (in Russian). DOI: 10.18500/0869-6632-2010-18-4-81-90.
  8. Smirnov DA, Mokhov II. From Granger causality to long-term causality: application to climatic data. Physical Review E. 2009;80:016208. DOI: 10.1103/PhysRevE.80.016208.
  9. Chaos and its Reconstruction. Eds. Gouesbet G, Meunier-Guttin-Cluzel G, Menard O. New York: Nova Science Publishers; 2003.
  10. Vlachos I, Kugiumtzis D. Nonuniform state-space reconstruction and coupling detection. Physical Review E. 2010;82:016207. DOI: 10.1103/PhysRevE.82.016207.
Received: 
21.11.2011
Accepted: 
20.03.2012
Published: 
29.06.2012
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