Type II General Exponential Class of Distributions

Hamedani, G. G.; Rasekhi, Mahdi; Najibi, Seyed Morteza; Yousof, Haitham M.; Alizadeh, Morad

doi:10.18187/pjsor.v15i2.1699

Cited by 44 publications

(23 citation statements)

References 17 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The * and * statistics are given by: * = (1 + 1/2 ) 1/(12 ) + , and: * = ( ) + , We compared the fits of the MOBE-2 distribution with some competitive models, namely: exponential (E (β)), odd Lindley exponential (OLiE), MO exponential (MOE (α, β)), moment exponential (MomE (β)), the logarithmic Burr-Hatke exponential (Log BrHE (β)), generalized MO exponential (GMOE (α, α, β)), beta exponential (BE (a, b, β)), MO-Kumaraswamy exponential (MOKwE (α, a, b, β)), Kumaraswamy exponential (KwE (a, b, β)), and Kumaraswamy MO exponential (KwMOE (α, a, b, β)). See the PDFs of the competitive moels in [21][22][23][24][25][26][27][28][29][30][31]. We considered the Cramér-Von Mises (W * ), the Anderson-Darling (A * ), and the Kolmogorov-Smirnov (KS) statistics.…”

Section: Data Imentioning

confidence: 99%

A New Flexible Three-Parameter Model: Properties, Clayton Copula, and Modeling Real Data

2020

View full text Add to dashboard Cite

In this article, we introduced a new extension of the binomial-exponential 2 distribution. We discussed some of its structural mathematical properties. A simple type Copula-based construction is also presented to construct the bivariate- and multivariate-type distributions. We estimated the model parameters via the maximum likelihood method. Finally, we illustrated the importance of the new model by the study of two real data applications to show the flexibility and potentiality of the new model in modeling skewed and symmetric data sets.

show abstract

Section: Data Imentioning

confidence: 99%

A New Flexible Three-Parameter Model: Properties, Clayton Copula, and Modeling Real Data

2020

View full text Add to dashboard Cite

show abstract

“…This subsection deals with the characterizations of BrXEW distribution based on the ratio of two truncated moments. Our first characterization employs a theorem due to Glänzel (1987), see Theorem 1 (see Hamedani et al (2018) and Hamedani et al (2019)). The result, however, holds also when the interval is not closed, since the condition of the Theorem is on the interior of .…”

Section: Characterizations Based On Two Truncated Momentsmentioning

confidence: 99%

The Burr X Exponentiated Weibull Model: Characterizations,Mathematical Properties and Applications to Failure and Survival Times Data

Khalil

Hamedani

Yousof

2019

Pak.j.stat.oper.res.

Self Cite

View full text Add to dashboard Cite

In this article, we introduce a new three-parameter lifetime model called the Burr X exponentiated Weibull model. The major justification for the practicality of the new lifetime model is based on the wider use of the exponentiated Weibull and Weibull models. We are motivated to propose this new lifetime model because it exhibits increasing, decreasing, bathtub, J shaped and constant hazard rates. The new lifetime model can be viewed as a mixture of the exponentiated Weibull distribution. It can also be viewed as a suitable model for fitting the right skewed, symmetric, left skewed and unimodal data. We provide a comprehensive account of some of its statistical properties. Some useful characterization results are presented. The maximum likelihood method is used to estimate the model parameters. We prove empirically the importance and flexibility of the new model in modeling two types of lifetime data. The proposed model is a better fit than the Poisson Topp Leone-Weibull, the Marshall Olkin extended-Weibull, gamma-Weibull , Kumaraswamy-Weibull , Weibull-Fréchet, beta-Weibull, transmuted modified-Weibull, Kumaraswamy transmuted- Weibull, modified beta-Weibull, Mcdonald-Weibull and transmuted exponentiated generalized-Weibull models so it is a good alternative to these models in modeling aircraft windshield data as well as the new lifetime model is much better than the Weibull-Weibull, odd Weibull-Weibull, Weibull Log-Weibull, the gamma exponentiated-exponential and exponential exponential-geometric models so it is a good alternative to these models in modeling the survival times of Guinea pigs. We hope that the new distribution will attract wider applications in reliability, engineering and other areas of research.

show abstract

“…Applying (11) to (10) for the term {− as scale parameter. The C-D-F of the P-BX-Fr can also be re-expressed as a mixture of Fr C-D-Fs given by ( , , , )…”

Section: Mathematical Properties 21 Useful Expansionsmentioning

confidence: 99%