Communications for Statistical Applications and Methods

The Korean Statistical Society (한국통계학회)
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Improving Sample Entropy Based on Nonparametric Quantile Estimation

  • Received : 20110300
  • Accepted : 20110500
  • Published : 2011.07.31
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Abstract

Sample entropy (Vasicek, 1976) has poor performance, and several nonparametric entropy estimators have been proposed as alternatives. In this paper, we consider a piecewise uniform density function based on quantiles, which enables us to evaluate entropy in each interval, and study the poor performance of the sample entropy in terms of the poor estimation of lower and upper quantiles. Then we propose some improved entropy estimators by simply modifying the quantile estimators, and compare their performances with some existing estimators.

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References

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