The Exponential Flexible Weibull Extension Distribution

El-Desouky, B. S.; Mustafa, Abdelfattah; AL-Garash, Shamsan

doi:10.4236/ojmsi.2017.51007

Cited by 13 publications

(7 citation statements)

References 19 publications

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“…Using the expression given in (9), El-Bassiouny et al [9], proposed a new lifetime distribution titled as EL distribution. Also, using the same technique El-Desouky et al [10], introduced another lifetime model named as The EFWEx distribution. By comparing (9) to (7) or (8), it is noted that the class characterized by (9) is a familiar general result in literature.…”

Section: Range Of T Members Of T-x Familymentioning

confidence: 99%

On Clarification to the Previously Published Research Articles

Ahmad¹

2017

IJTAM

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In the recent literature, attempts have been made to propose new statistical distributions for modeling real phenomena of nature by adding one or more additional shape parameter (s) to the distribution of baseline random variable. The major contribution of these distributions are to obtain monotonic and non-monotonic shaped failure rates. This short article, offers a clarification to the research articles proposed by Al-Kadim and Boshi [4], El-Bassiouny et al. [9] and El-Desouky et al. [10]. A brief discussion on the properties of this general class is given. A future research motivation on this subject is also provided.

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Section: Range Of T Members Of T-x Familymentioning

confidence: 99%

On Clarification to the Previously Published Research Articles

Ahmad¹

2017

IJTAM

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“…Table (4) displays the results of fitting multiple lifetime distributions to the Aarset data. The competitive distributions are the additive Weibull (AddW) in [24], the WEM in [6], the modified Weibull in [25], the exponential flexible Weibull Extension (EFWE) distribution in [3], the two-component mixtures of three-parameter Weibull (M3pW) (see, [11]), exponentiated Weibull (MEW) (common scale parameters in both components) (see, [26]), Burr type III (MBurrIII) (see, [27]) and WEM are fitted as well. A reduced version of MWEM is the two-component mixture of the Chen model when the scale parameter 𝛽 = 1 for both components (MWEMR1).…”

Section: Discussionmentioning

confidence: 99%

“…They derived various structural properties and MLEs for the new modified distribution. Reference [3] studied a new generalization of the flexible Weibull distribution with three parameters referred to as the exponentiated flexible Weibull extension. Their new distribution exhibits bathtub shape hazard rate function.…”

Section: Introductionmentioning

confidence: 99%

Study of the New Finite Mixture of Weibull Extension Model: Identifiability, Properties and Estimation

Mohamed¹,

Ismail²,

Ismail³

2022

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Finite mixture models have been used in many fields of statistical analysis such as pattern recognition, clustering and survival analysis, and have been extensively applied in different scientific areas such as marketing, economics, medicine, genetics and social sciences. Introducing mixtures of new generalized lifetime distributions that exhibit important hazard shapes is a major field of research aiming at fitting and analyzing a wider variety of data sets. The main objective of this article is to present a full mathematical study of the properties of the new finite mixture of the three-parameter Weibull extension model, considered as a generalization of the standard Weibull distribution. The new proposed mixture model exhibits a bathtub-shaped hazard rate among other important shapes in reliability applications. We analytically prove the identifiability of the new mixture and investigate its mathematical properties and hazard rate function. Maximum likelihood estimation of the model parameters is considered. The Kolmogrov-Smirnov test statistic is used to fit two famous data sets from mechanical engineering to the proposed model, the Aarset data and the Meeker and Escobar datasets. Results show that the two-component version of the proposed mixture is a superior fit compared to various lifetime distributions, either one-component or two-component lifetime distributions. The new proposed mixture is a significant statistical tool to study lifetime data sets in numerous fields of study.

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“…The second data set (we set out to represent it with Data 2) shows the failure time of the electronic reactor pumps. More detail about this data can be found in [25] . The waiting time is measured in hours.…”

Section: Applicationsmentioning

confidence: 99%

A new probabilistic model: Theory, simulation and applications to sports and failure times data

Tang,

Seong,

Alharbi

et al. 2024

Heliyon

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The Exponential Flexible Weibull Extension Distribution

Cited by 13 publications

References 19 publications

On Clarification to the Previously Published Research Articles

On Clarification to the Previously Published Research Articles

Study of the New Finite Mixture of Weibull Extension Model: Identifiability, Properties and Estimation

A new probabilistic model: Theory, simulation and applications to sports and failure times data

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