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Published in:
01-06-2015
Entropy Estimation Using Numerical Methods
Published in: Annals of Data Science | Issue 2/2015
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Abstract
Direct integration of the Riemann–Stieltjes integral has been used to computing convolution integrals. This approach has been established to be simple and accurate with good convergence property. In this paper, we used some numerical methods to estimation of entropy of a continuous random variable and then some estimators are introduced. Bounds on the error terms are derived for some direct Riemann–Stieltjes integration methods. Consistency of estimators is proved and by simulation, the proposed estimators are compared with some prominent estimators, namely Correa (Commun Stat Theory Methods 24:2439–2449, 1995), Ebrahimi et al. (Stat Probab Lett 20:225–234, 1994), van Es (Scand J Stat 19:61–72, 1992) and Vasicek (J R Stat Soc B 38:54–59, 1976). The results indicate that the proposed estimators have smaller mean squared error than other estimators.