Computing Accurate Probabilistic Estimates of One-D Entropy from Equiprobable Random Samples

Computing Accurate Probabilistic Estimates of One-D Entropy from Equiprobable Random Samples

We develop a simple Quantile Spacing (QS) method for accurate probabilistic estimation of one-dimensional entropy from equiprobable random samples, and compare it with the popular Bin-Counting (BC) and Kernel Density (KD) methods. In contrast to BC, which uses equal-width bins with varying probabili...

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Bibliographic Details
Main Authors: Hoshin V. Gupta, Mohammad Reza Ehsani, Tirthankar Roy, Maria A. Sans-Fuentes, Uwe Ehret, Ali Behrangi
Format: Article
Language:English
Published: MDPI AG 2021-06-01
Series:Entropy
Subjects:
entropy
estimation
quantile spacing
accuracy
uncertainty
bootstrap
Online Access:https://www.mdpi.com/1099-4300/23/6/740

Internet

https://www.mdpi.com/1099-4300/23/6/740

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