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Título:
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Auto-association measures for stationary time seriesof categorical data.
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Autores:
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Biswas, Atanu ;
Pardo Llorente, María del Carmen
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Tipo de documento:
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texto impreso
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Editorial:
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Springer, 2014
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Dimensiones:
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application/pdf
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Nota general:
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info:eu-repo/semantics/restrictedAccess
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Idiomas:
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Palabras clave:
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Estado = Publicado
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Materia = Ciencias: Matemáticas: Estadística matemática
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Tipo = Artículo
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Resumen:
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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.
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En línea:
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https://eprints.ucm.es/37278/1/PardoCarmen26.pdf
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