@article{Mohamed2023, 
author = {Mohamed Said Mohamed and Najwan Alsadat and Oluwafemi Samson Balogun},
title = {Continuous Tsallis and Renyi extropy with pharmaceutical market application},
year = {2023},
journal = {AIMS Mathematics},
volume = {8},
number = {10},
pages = {24176-24195},
keywords = {extropy, Tsallis entropy, Renyi entropy, non-parametric estimation, time series},
url = {https://www.sciopen.com/article/10.3934/math.20231233},
doi = {10.3934/math.20231233},
abstract = {In this paper, the Tsallis and Renyi extropy is presented as a continuous measure of information under the continuous distribution. Furthermore, the features and their connection to other information measures are introduced. Some stochastic comparisons and results on the order statistics and upper records are given. Moreover, some theorems about the maximum Tsallis and Renyi extropy are discussed. On the other hand, numerical results of the non-parametric estimation of Tsallis extropy are calculated for simulated and real data with application to time series model and its forecasting.}
}