Some new findings on the survival Rényi entropy and application of COVID-19 data

Mohamed, Mohamed Said; Almohaimeed, Amani; El‐Raouf, M. M. Abd

doi:10.1016/j.rinp.2021.104966

Cited by 3 publications

(1 citation statement)

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“…The literature teems with several results of the Shannon entropy and its related measures. Interested readers may refer to [14][15][16][17][18] for the Shannon entropy, Kullback-Leibler divergence, and Fisher information number; [19,20] for fractional cumulative residual entropy and cumulative residual entropy, respectively; [13,[21][22][23][24] for the Tsallis entropy and its related measures; and finally [25,26] for the extropy and Rényi entropy and its applications, respectively.…”

Section: Introductionmentioning

confidence: 99%

Cumulative Residual Tsallis Entropy-Based Test of Uniformity and Some New Findings

et al. 2022

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The Tsallis entropy is an extension of the Shannon entropy and is used extensively in physics. The cumulative residual Tsallis entropy, which is a generalization of the Tsallis entropy, plays an important role in the measurement uncertainty of random variables and has simple relationships with other important information and reliability measures. In this paper, some novel properties of the cumulative residual Tsallis entropy are disclosed. Moreover, this entropy measure is applied to testing the uniformity, where the limit distribution and an approximation of the distribution of the test statistic are derived. In addition, the property of stability is discussed. Furthermore, the percentage points and power against seven alternative distributions of this test statistic are presented. Finally, to compare the power of the suggested test with that of other tests of uniformity, a simulation study is conducted.

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Section: Introductionmentioning

confidence: 99%

Cumulative Residual Tsallis Entropy-Based Test of Uniformity and Some New Findings

et al. 2022

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The Approach of Machine Learning to Optimize the Bank-Customer Interaction at Pandemic Epochs

Nieto-Chaupis¹

2022

2022 IEEE/ACIS 23rd International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distribu

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Some new results involving residual Renyi's information measure for $ k $-record values

Shrahili

2024

MATH

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<abstract><p>This article dealt with further properties of the Renyi entropy and the residual Renyi entropy of $ k $-record values. First, we discussed the Renyi entropy order and its connection with the usual stochastic and dispersive orders. We then addressed the monotonicity properties of the residual Renyi entropy of $ k $-records, focusing on the aging properties of the component lifetimes. We also expressed the residual $ n $th upper $ k $-records in terms of Renyi entropy when the first dataset exceeded a certain threshold, and then studied various properties of the given formula. Finally, we conducted a parametric estimation of the Renyi entropy of the $ n $th upper $ k $-records. The estimation was performed using both real COVID-19 data and simulated data.</p></abstract>

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Some new findings on the survival Rényi entropy and application of COVID-19 data

Cited by 3 publications

References 23 publications

Cumulative Residual Tsallis Entropy-Based Test of Uniformity and Some New Findings

Cumulative Residual Tsallis Entropy-Based Test of Uniformity and Some New Findings

The Approach of Machine Learning to Optimize the Bank-Customer Interaction at Pandemic Epochs

Some new results involving residual Renyi's information measure for $ k $-record values

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