The Beta Generalized Inverse Weibull Geometric Distribution

Elbatal, İbrahim; Gebaly, Yehia M. El; Amin, Essam A.

doi:10.18187/pjsor.v13i1.1791

Cited by 12 publications

(8 citation statements)

References 6 publications

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“…For these data, we compare the TIHLIW model with some rival models, namely, the beta generalized inverse Weibull geometric (BGIWGc) by Elbatal et al [26], transmuted complementary Weibull geometric (TCWGc) by Afify et al [27], beta transmuted Weibull (BTW) by Afify et al [28], McDonald log-logistic (McLL) by Tahir et al [29], beta Weibull (BW) by Lee et al [30], McDonald Weibull (McW) by Cordeiro et al [31], exponentiated transmuted generalized Rayleigh (ETGR) by Afify et al [32], and new modified Weibull (NMW) [33] distributions. e PDFs of these distributions are given (for x > 0) by…”

Section: Discussionmentioning

confidence: 99%

The Extended Inverse Weibull Distribution: Properties and Applications

et al. 2020

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This paper proposes the new three-parameter type I half-logistic inverse Weibull (TIHLIW) distribution which generalizes the inverse Weibull model. The density function of the TIHLIW can be expressed as a linear combination of the inverse Weibull densities. Some mathematical quantities of the proposed TIHLIW model are derived. Four estimation methods, namely, the maximum likelihood, least squares, weighted least squares, and Cramér–von Mises methods, are utilized to estimate the TIHLIW parameters. Simulation results are presented to assess the performance of the proposed estimation methods. The importance of the TIHLIW model is studied via a real data application.

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Section: Discussionmentioning

confidence: 99%

The Extended Inverse Weibull Distribution: Properties and Applications

et al. 2020

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“…In order to compare the OFrL model with other fitted distributions has four, five and six parameters. we compare the fits of the OFrL distribution with the beta generalized inverse Weibull geometric distribution (BGIWGc) ( Elbatal et al, 2017), beta transmuted Weibull (BTW) (Afify et al, 2017), McDonald log-logistic (McLL) (Tahir et al, 2014), McDonald Weibull (McW) (Cordeiro et al, 2014), new modified Weibull (NMW) (Almalki and Yuan, 2013), transmuted complementary Weibull-geometric (TCWG) (Afify et al, 2014), beta Weibull (BW) (Lee et al, 2007) and exponentiated transmuted generalized Rayleigh (ETGR) (Afify et al, 2015) distributions.…”

Section: Applicationmentioning

confidence: 99%

Statistical properties of Odd Frѐchet Lomax Distribution

2019

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A new lifetime distribution with three parameters, called odd Frѐchet Lomax (OFrL), is introduced. Some statistical properties of the OFrL are provided. Explicit expressions for the quntile, moments, moment generating function, probability weighted moments and order statistics are studied. Maximum likelihood estimation technique is employed to estimate the model parameters are studied. In addition, the superiority of the OFrL distribution is illustrated with applications to one real data set.

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“…We compare the fits of the OFIR distribution with the beta generalized inverse Weibull geometric distribution (BGIWGc) ( Elbatal et al, [7]), beta transmuted Weibull (BTW) (Afify et al, [3]), McDonald log-logistic (McLL) (Tahir et al, [18]), McDonald Weibull (McW) (Cordeiro et al, [6]), new modified Weibull (NMW) (Almalki and Yuan, [5]), transmuted complementary Weibull-geometric (TCWG) (Afify et al, [1]), beta Weibull (BW) (Lee et al, [17]), and exponentiated transmuted generalized Rayleigh (ETGR) (Afify et al, [2]) distributions.…”

Section: Applicationmentioning

confidence: 99%