Preprint Article Version 1 Preserved in Portico This version is not peer-reviewed

Uncertainty Quantification Based on Residual Tsallis Entropy of Order Statistics

Version 1 : Received: 21 September 2023 / Approved: 21 September 2023 / Online: 22 September 2023 (11:09:46 CEST)

How to cite: Shrahili, M.; Kayid, M. Uncertainty Quantification Based on Residual Tsallis Entropy of Order Statistics. Preprints 2023, 2023091495. https://doi.org/10.20944/preprints202309.1495.v1 Shrahili, M.; Kayid, M. Uncertainty Quantification Based on Residual Tsallis Entropy of Order Statistics. Preprints 2023, 2023091495. https://doi.org/10.20944/preprints202309.1495.v1

Abstract

In this paper, we concentrate on the study of the properties of residual Tsallis entropy for order statistics. Order statistics have an important role in reliability structural engineering for example for modelling lifetimes of series and parallel systems. The residual Tsallis entropy of ith order statistic from a continuous distribution function and its deviation from the residual Tsallis entropy of ith order statistics from a uniform distribution is investigated. In a mathematical framework, a method to express the residual Tsallis entropy of the ith order statistic from a continuous distribution in terms of the residual Tsallis entropy of the ith order statistic from a uniform distribution is provided. This approach may provide insight into the behavior and properties of the residual Tsallis entropy for order statistics. Further, we study the monotonicity properties of the residual Tsallis entropy of order statistics under di erent conditions. By studying these properties, deeper understanding of the relationship between the position of order statistics and the resulting residual Tsallis entropy is gained.

Keywords

order statistics; residual Tsallis entropy; Shannon entropy; residual lifetime; (n-i+1)-out-of-n system

Subject

Engineering, Civil Engineering

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