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Entropy Estimation Using Numerical Methods

机译:数值方法的熵估计

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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.
机译:Riemann-Stieltjes积分的直接积分已用于计算卷积积分。已经建立了这种方法,该方法简单,准确且具有良好的收敛性。在本文中,我们使用一些数值方法来估计连续随机变量的熵,然后介绍了一些估计器。对于某些直接的Riemann-Stieltjes积分方法,可以得出误差项的界线。证明了估计量的一致性,并且通过仿真,将提出的估计量与一些著名的估计量进行比较,这些估计量为Correa(Commun Stat Theory Methods 24:2439-2449,1995),Ebrahimi等。 (Stat Probab Lett 20:225-234,1994),van Es(Scand J Stat 19:61-72,1992)和Vasicek(J R Stat Soc B 38:54-59,1976)。结果表明,提出的估计量具有比其他估计量小的均方误差。

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