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Macroscopic characterization of data sets by using the average absolute deviation

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  • Campos, Diógenes

Abstract

This paper describes a method for getting a synthesis of the knowledge about a given system, assuming that a data set x of measurements of a variable Ξ is known: i.e., separate data are combined in order to form a coherent whole, à la thermodynamics. For getting the macroscopic characterization of time series data, one takes advantage of the average absolute deviation concept together with an already known thermodynamic-like approach.

Suggested Citation

  • Campos, Diógenes, 2014. "Macroscopic characterization of data sets by using the average absolute deviation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 393(C), pages 222-234.
  • Handle: RePEc:eee:phsmap:v:393:y:2014:i:c:p:222-234
    DOI: 10.1016/j.physa.2013.09.013
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    References listed on IDEAS

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    3. Campos, Diógenes, 2011. "A thermodynamic-like approach for the study of probabilistic systems," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(2), pages 214-222.
    4. Campos, Diógenes, 2012. "On a modified quantum statistical mechanics based on the Hartley information," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(22), pages 5439-5452.
    5. Gonzalez, J.L. & de Faria, E.L. & Albuquerque, Marcelo P. & Albuquerque, Marcio P., 2011. "Nonadditive Tsallis entropy applied to the Earth’s climate," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(4), pages 587-594.
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