Product of spacing estimation of entropy for inverse Weibull distribution under progressive type-II censored data with applications

This paper seeks to estimate the entropy for the inverse Weibull distribution using progressively Type-II censored data. To reach this objective, the entropy is defined through three entropy measures, namely, Rényi, q-entropy and Shannon entropy, and two estimation methods are used to estimate them....
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Gespeichert in:

Autor*in:	Hassan Okasha [verfasserIn] Mazen Nassar [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2022

Schlagwörter:	Inverse Weibull distribution maximum likelihood estimation maximum product of spacing estimation Rényi entropy Shannon entropy

Übergeordnetes Werk:	In: Journal of Taibah University for Science - Taylor & Francis Group, 2016, 16(2022), 1, Seite 259-269
Übergeordnetes Werk:	volume:16 ; year:2022 ; number:1 ; pages:259-269

Links:	Link aufrufen Link aufrufen Link aufrufen Journal toc

DOI / URN:	10.1080/16583655.2022.2046945

Katalog-ID:	DOAJ00430263X

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spelling	10.1080/16583655.2022.2046945 doi (DE-627)DOAJ00430263X (DE-599)DOAJ795a1fda3d2d48f5a6d5baa5a040d9e5 DE-627 ger DE-627 rakwb eng Q1-390 Hassan Okasha verfasserin aut Product of spacing estimation of entropy for inverse Weibull distribution under progressive type-II censored data with applications 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier This paper seeks to estimate the entropy for the inverse Weibull distribution using progressively Type-II censored data. To reach this objective, the entropy is defined through three entropy measures, namely, Rényi, q-entropy and Shannon entropy, and two estimation methods are used to estimate them. The first approach to estimate these quantities is the method of maximum likelihood. Furthermore, and for the first time, we consider the method of maximum product of spacing to estimate the mentioned entropy measures. Also, a simulation study is carried out and two real data sets are analysed. The numerical outcomes showed that the maximum likelihood provides good point estimates while the interval estimates based on the maximum product of spacing method have the shortest confidence interval lengths. Inverse Weibull distribution maximum likelihood estimation maximum product of spacing estimation Rényi entropy Shannon entropy Science (General) Mazen Nassar verfasserin aut In Journal of Taibah University for Science Taylor & Francis Group, 2016 16(2022), 1, Seite 259-269 (DE-627)835589021 (DE-600)2834710-9 16583655 nnns volume:16 year:2022 number:1 pages:259-269 https://doi.org/10.1080/16583655.2022.2046945 kostenfrei https://doaj.org/article/795a1fda3d2d48f5a6d5baa5a040d9e5 kostenfrei https://www.tandfonline.com/doi/10.1080/16583655.2022.2046945 kostenfrei https://doaj.org/toc/1658-3655 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 16 2022 1 259-269
allfields_unstemmed	10.1080/16583655.2022.2046945 doi (DE-627)DOAJ00430263X (DE-599)DOAJ795a1fda3d2d48f5a6d5baa5a040d9e5 DE-627 ger DE-627 rakwb eng Q1-390 Hassan Okasha verfasserin aut Product of spacing estimation of entropy for inverse Weibull distribution under progressive type-II censored data with applications 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier This paper seeks to estimate the entropy for the inverse Weibull distribution using progressively Type-II censored data. To reach this objective, the entropy is defined through three entropy measures, namely, Rényi, q-entropy and Shannon entropy, and two estimation methods are used to estimate them. The first approach to estimate these quantities is the method of maximum likelihood. Furthermore, and for the first time, we consider the method of maximum product of spacing to estimate the mentioned entropy measures. Also, a simulation study is carried out and two real data sets are analysed. The numerical outcomes showed that the maximum likelihood provides good point estimates while the interval estimates based on the maximum product of spacing method have the shortest confidence interval lengths. Inverse Weibull distribution maximum likelihood estimation maximum product of spacing estimation Rényi entropy Shannon entropy Science (General) Mazen Nassar verfasserin aut In Journal of Taibah University for Science Taylor & Francis Group, 2016 16(2022), 1, Seite 259-269 (DE-627)835589021 (DE-600)2834710-9 16583655 nnns volume:16 year:2022 number:1 pages:259-269 https://doi.org/10.1080/16583655.2022.2046945 kostenfrei https://doaj.org/article/795a1fda3d2d48f5a6d5baa5a040d9e5 kostenfrei https://www.tandfonline.com/doi/10.1080/16583655.2022.2046945 kostenfrei https://doaj.org/toc/1658-3655 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 16 2022 1 259-269
allfieldsGer	10.1080/16583655.2022.2046945 doi (DE-627)DOAJ00430263X (DE-599)DOAJ795a1fda3d2d48f5a6d5baa5a040d9e5 DE-627 ger DE-627 rakwb eng Q1-390 Hassan Okasha verfasserin aut Product of spacing estimation of entropy for inverse Weibull distribution under progressive type-II censored data with applications 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier This paper seeks to estimate the entropy for the inverse Weibull distribution using progressively Type-II censored data. To reach this objective, the entropy is defined through three entropy measures, namely, Rényi, q-entropy and Shannon entropy, and two estimation methods are used to estimate them. The first approach to estimate these quantities is the method of maximum likelihood. Furthermore, and for the first time, we consider the method of maximum product of spacing to estimate the mentioned entropy measures. Also, a simulation study is carried out and two real data sets are analysed. The numerical outcomes showed that the maximum likelihood provides good point estimates while the interval estimates based on the maximum product of spacing method have the shortest confidence interval lengths. Inverse Weibull distribution maximum likelihood estimation maximum product of spacing estimation Rényi entropy Shannon entropy Science (General) Mazen Nassar verfasserin aut In Journal of Taibah University for Science Taylor & Francis Group, 2016 16(2022), 1, Seite 259-269 (DE-627)835589021 (DE-600)2834710-9 16583655 nnns volume:16 year:2022 number:1 pages:259-269 https://doi.org/10.1080/16583655.2022.2046945 kostenfrei https://doaj.org/article/795a1fda3d2d48f5a6d5baa5a040d9e5 kostenfrei https://www.tandfonline.com/doi/10.1080/16583655.2022.2046945 kostenfrei https://doaj.org/toc/1658-3655 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 16 2022 1 259-269
allfieldsSound	10.1080/16583655.2022.2046945 doi (DE-627)DOAJ00430263X (DE-599)DOAJ795a1fda3d2d48f5a6d5baa5a040d9e5 DE-627 ger DE-627 rakwb eng Q1-390 Hassan Okasha verfasserin aut Product of spacing estimation of entropy for inverse Weibull distribution under progressive type-II censored data with applications 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier This paper seeks to estimate the entropy for the inverse Weibull distribution using progressively Type-II censored data. To reach this objective, the entropy is defined through three entropy measures, namely, Rényi, q-entropy and Shannon entropy, and two estimation methods are used to estimate them. The first approach to estimate these quantities is the method of maximum likelihood. Furthermore, and for the first time, we consider the method of maximum product of spacing to estimate the mentioned entropy measures. Also, a simulation study is carried out and two real data sets are analysed. The numerical outcomes showed that the maximum likelihood provides good point estimates while the interval estimates based on the maximum product of spacing method have the shortest confidence interval lengths. Inverse Weibull distribution maximum likelihood estimation maximum product of spacing estimation Rényi entropy Shannon entropy Science (General) Mazen Nassar verfasserin aut In Journal of Taibah University for Science Taylor & Francis Group, 2016 16(2022), 1, Seite 259-269 (DE-627)835589021 (DE-600)2834710-9 16583655 nnns volume:16 year:2022 number:1 pages:259-269 https://doi.org/10.1080/16583655.2022.2046945 kostenfrei https://doaj.org/article/795a1fda3d2d48f5a6d5baa5a040d9e5 kostenfrei https://www.tandfonline.com/doi/10.1080/16583655.2022.2046945 kostenfrei https://doaj.org/toc/1658-3655 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 16 2022 1 259-269
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callnumber-first	Q - Science
author	Hassan Okasha
spellingShingle	Hassan Okasha misc Q1-390 misc Inverse Weibull distribution misc maximum likelihood estimation misc maximum product of spacing estimation misc Rényi entropy misc Shannon entropy misc Science (General) Product of spacing estimation of entropy for inverse Weibull distribution under progressive type-II censored data with applications
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topic_title	Q1-390 Product of spacing estimation of entropy for inverse Weibull distribution under progressive type-II censored data with applications Inverse Weibull distribution maximum likelihood estimation maximum product of spacing estimation Rényi entropy Shannon entropy
topic	misc Q1-390 misc Inverse Weibull distribution misc maximum likelihood estimation misc maximum product of spacing estimation misc Rényi entropy misc Shannon entropy misc Science (General)
topic_unstemmed	misc Q1-390 misc Inverse Weibull distribution misc maximum likelihood estimation misc maximum product of spacing estimation misc Rényi entropy misc Shannon entropy misc Science (General)
topic_browse	misc Q1-390 misc Inverse Weibull distribution misc maximum likelihood estimation misc maximum product of spacing estimation misc Rényi entropy misc Shannon entropy misc Science (General)
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title	Product of spacing estimation of entropy for inverse Weibull distribution under progressive type-II censored data with applications
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title_full	Product of spacing estimation of entropy for inverse Weibull distribution under progressive type-II censored data with applications
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title_sort	product of spacing estimation of entropy for inverse weibull distribution under progressive type-ii censored data with applications
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title_auth	Product of spacing estimation of entropy for inverse Weibull distribution under progressive type-II censored data with applications
abstract	This paper seeks to estimate the entropy for the inverse Weibull distribution using progressively Type-II censored data. To reach this objective, the entropy is defined through three entropy measures, namely, Rényi, q-entropy and Shannon entropy, and two estimation methods are used to estimate them. The first approach to estimate these quantities is the method of maximum likelihood. Furthermore, and for the first time, we consider the method of maximum product of spacing to estimate the mentioned entropy measures. Also, a simulation study is carried out and two real data sets are analysed. The numerical outcomes showed that the maximum likelihood provides good point estimates while the interval estimates based on the maximum product of spacing method have the shortest confidence interval lengths.
abstractGer	This paper seeks to estimate the entropy for the inverse Weibull distribution using progressively Type-II censored data. To reach this objective, the entropy is defined through three entropy measures, namely, Rényi, q-entropy and Shannon entropy, and two estimation methods are used to estimate them. The first approach to estimate these quantities is the method of maximum likelihood. Furthermore, and for the first time, we consider the method of maximum product of spacing to estimate the mentioned entropy measures. Also, a simulation study is carried out and two real data sets are analysed. The numerical outcomes showed that the maximum likelihood provides good point estimates while the interval estimates based on the maximum product of spacing method have the shortest confidence interval lengths.
abstract_unstemmed	This paper seeks to estimate the entropy for the inverse Weibull distribution using progressively Type-II censored data. To reach this objective, the entropy is defined through three entropy measures, namely, Rényi, q-entropy and Shannon entropy, and two estimation methods are used to estimate them. The first approach to estimate these quantities is the method of maximum likelihood. Furthermore, and for the first time, we consider the method of maximum product of spacing to estimate the mentioned entropy measures. Also, a simulation study is carried out and two real data sets are analysed. The numerical outcomes showed that the maximum likelihood provides good point estimates while the interval estimates based on the maximum product of spacing method have the shortest confidence interval lengths.
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title_short	Product of spacing estimation of entropy for inverse Weibull distribution under progressive type-II censored data with applications
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Product of spacing estimation of entropy for inverse Weibull distribution under progressive type-II censored data with applications

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