Weighted extropies and past extropy of order statistics and <i>k</i>-record values

Bansal, Shilpa; Gupta, Nitin

doi:10.1080/03610926.2020.1853773

Cited by 15 publications

(4 citation statements)

References 22 publications

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“…The entropy value method is an important application of entropy theory in the field of determining weight [49,50]. The degree of dispersion and the importance of analysis of each evaluation index can be judged by the entropy value and the weight of the index [51,52]. Generally, the smaller the entropy value, the greater the variation degree of the index value, the greater the weight coefficient, the more information provided, the greater the role played in the comprehensive evaluation, and vice versa [52,53].…”

Section: Entropy Value Methodsmentioning

confidence: 99%

Coordination of agricultural informatization and agricultural economy development: A panel data analysis from Shandong Province, China

Sun

Zhao

2022

PLoS ONE

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With the continuous development of the world economy, science, and technology, the era of intelligence and information is upon us. Through the implementation of the digital rural construction project in China, agriculture is developing rapidly in the direction of informatization. As a major agricultural province in China, Shandong Province has been ranked first in China for many years in terms of gross agricultural product and the import and export of agricultural products. According to the current situation of agricultural informatization in Shandong Province, this study uses relevant evaluation index data of Shandong Province from 2011 to 2019 and applies the entropy value method, coupling degree analysis model, and coupling coordination degree analysis model to deeply evaluate the mutual influence and coordination degree between the agricultural informatization level and agricultural economic development in Shandong province in each year. We identify the possible problems in the development of agricultural informatization in Shandong province. Finally, in terms of talent construction, infrastructure construction, the main role of government, policies, and farmers’ awareness of informatization, we propose some countermeasures and suggestions that are conducive to the coordinated development of agricultural informatization and the agricultural economy.

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Section: Entropy Value Methodsmentioning

confidence: 99%

Coordination of agricultural informatization and agricultural economy development: A panel data analysis from Shandong Province, China

Sun

Zhao

2022

PLoS ONE

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“…Sudheesh and Sreedevi (2022) [38] discussed non-parametric estimation of CRJ (X) and CJ (X) for right-censored data. Recently, Balakrishnan et al [29], Bansal and Gupta [39] and Sathar and Nair [40][41][42] introduced different weighted versions of extropy. The weighted version of the survival extropy is given by [41] J(X, w) = − 1 2 ∞ 0…”

Section: Connection Between Entropy and Extropymentioning

confidence: 99%

A Generalized Measure of Cumulative Residual Entropy

Kattumannil

Sreedevi²

2022

Entropy

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In this work, we introduce a generalized measure of cumulative residual entropy and study its properties. We show that several existing measures of entropy, such as cumulative residual entropy, weighted cumulative residual entropy and cumulative residual Tsallis entropy, are all special cases of this generalized cumulative residual entropy. We also propose a measure of generalized cumulative entropy, which includes cumulative entropy, weighted cumulative entropy and cumulative Tsallis entropy as special cases. We discuss a generating function approach, using which we derive different entropy measures. We provide residual and cumulative versions of Sharma–Taneja–Mittal entropy and obtain them as special cases this generalized measure of entropy. Finally, using the newly introduced entropy measures, we establish some relationships between entropy and extropy measures.

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“…For the choice of w(u) = 1/2 and φ(x) = x, G f re (2) reduces to the weighted cumulative residual entropy of Mirali et al (2016).…”

Section: Generating Functionmentioning

confidence: 99%

A Generalized Measure of Cumulative Residual Entropy

Kattumannil¹,

Sreedevi²

2022

Preprint

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In this work, we introduce a generalized measure of cumulative residual entropy and study its properties. We show that several existing measures of entropy such as cumulative residual entropy, weighted cumulative residual entropy and cumulative residual Tsallis entropy, are all special cases of the generalized cumulative residual entropy. We also propose a measure of generalized cumulative entropy, which includes cumulative entropy, weighted cumulative entropy and cumulative Tsallis entropy as special cases. We discuss generating function approach using which we derive different entropy measures. Finally, using the newly introduced entropy measures, we establish some relationships between entropy and extropy measures.

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Weighted extropies and past extropy of order statistics and k-record values

Cited by 15 publications

References 22 publications

Coordination of agricultural informatization and agricultural economy development: A panel data analysis from Shandong Province, China

Coordination of agricultural informatization and agricultural economy development: A panel data analysis from Shandong Province, China

A Generalized Measure of Cumulative Residual Entropy

A Generalized Measure of Cumulative Residual Entropy

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