A New Estimator for Shannon Entropy

Authors

  • Havva Alizadeh Noughabi Department of Computer Engineering, University of Gonabad, Gonabad, Iran
  • Jalil Jarrahiferiz Department of Mathematics, Birjand Branch, Islamic Azad University, Birjand, Iran

Keywords:

Information theory, sample entropy, spacings, local linear model, mean squared error

Abstract

In this paper, we propose a new estimator for Shannon entropy of a continuous random variable. Consistency and other properties of the new estimator is stated. Through a Monte Carlo simulation, the mean squared error of the proposed estimator is compared with some prominent estimators, namely Vasicek’s estimator, Van Es’s estimator, and Correa’s estimator. Finally, it is shown that the proposed estimator has smaller mean squared error than the other estimators.

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Published

2019-07-10

How to Cite

Noughabi, H. A., & Jarrahiferiz, J. (2019). A New Estimator for Shannon Entropy. Thailand Statistician, 17(2), 190–197. Retrieved from https://ph02.tci-thaijo.org/index.php/thaistat/article/view/202290

Issue

Vol. 17 No. 2 (2019): July

Section

Articles