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    Auto-Havra Charvat entropic measures for stationary time series of categorical data

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    Date
    2013-05
    Author
    Biswas, Atanu
    Pardo, Maria del Carmen
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    Abstract
    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. One can alternatively think of using some entropic measures, of which a measure introduced by Havrda and Charvat (1967) could be particularly useful. We discuss some theoretical properties of measures from this class in the context of categorical time series and look at specific examples. Theoretical properties and simulation results are given along with an illustrative real data example.
    URI
    http://hdl.handle.net/11718/23775
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