Auto-association measures for stationary time series of categorical data

• Atanu Biswas ^[1] ; Maria del Carmen Pardo ^[2] ; Apratim Guha ^[3]
  1. [1] Indian Statistical Institute

     Indian Statistical Institute

     India

     
  2. [2] Universidad Complutense de Madrid

     Universidad Complutense de Madrid

     Madrid, España

     
  3. [3] Indian Institute of Management, Ahmedabad

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• Localización: Test: An Official Journal of the Spanish Society of Statistics and Operations Research, ISSN-e 1863-8260, ISSN 1133-0686, Vol. 23, Nº. 3, 2014, págs. 487-514
• Idioma: inglés
• DOI: 10.1007/s11749-014-0364-8
• Texto completo no disponible (Saber más ...)
• Resumen

  • For stationary time series of nominal categorical data or ordinal categorical data (with arbitrary ordered numberings of the categories), autocorrelation does not make much sense. Biswas and Guha (J Stat Plan Infer 139:3076–3087, 2009a) used mutual information as a measure of association and introduced the concept of auto-mutual information in this context. In this present paper, we introduce general auto-association measures for this purpose and study several special cases. Theoretical properties and simulation results are given along with two illustrative real data examples