Ba, Amadou Diadie and Lo, Gane Samb (2021) Joint-Conditional Entropy and Mutual Information Estimation Involving Three Random Variables and asymptotic Normality. In: Theory and Practice of Mathematics and Computer Science Vol. 11. B P International, pp. 15-38. ISBN 978-93-91215-41-5
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Official URL: https://doi.org/10.9734/bpi/tpmcs/v11/8228D
Abstract
A method of estimating the joint probability mass function of a triplet of discrete random variables is described. This estimator is used to construct the joint-conditional entropies and mutual information estimates involving three random variables. From there almost sure rates of convergence and asymptotic normality are established. The theorical results are validated by simulations.
| Item Type: | Book Section |
|---|---|
| Subjects: | STM Academic > Computer Science |
| Depositing User: | Unnamed user with email support@stmacademic.com |
| Date Deposited: | 07 Dec 2023 04:35 |
| Last Modified: | 07 Dec 2023 04:35 |
| URI: | http://article.researchpromo.com/id/eprint/1593 |
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