Exp-Uniform Distribution: Properties and Characterizations

This article uses the odd Lomax-G family of distributions to study a new extension of the Kumaraswamy distribution called “odd Lomax-Kumaraswamy distribution”. In this article, the density and distribution functions of the odd Lomax-Kumaraswamy distribution are defined and studied with many other properties of the distribution such as the ordinary moments, moment generating function, characteristic function, quantile function, reliability functions, order statistics and other useful measures. The model parameters are estimated by the method of maximum likelihood. The goodness-of-fit of the proposed distribution is demonstrated using two real data sets.

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“…Collecting like terms in equation (24) and simplifying the result, the quantile function of the OLomKumD is obtained as:…”

Section: Quantile Function Median and Simulationmentioning

confidence: 99%

“…These families of distribution have also led to the development of some generalizations of the Kumaraswamy distribution in the literature such as the transmuted Kumaraswamy distribution [23], the exponentiated Kumaraswamy distribution [24], the Kumaraswamy-Kumaraswamy distribution [25] and the Lomax-Kumaraswamy distribution [26].…”

Section: Introductionmentioning

confidence: 99%

Odd Lomax-Kumaraswamy Distribution: Its Properties and Applications

Yakura¹,

Sule

Dewu³

et al. 2020

JSRR

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“…In order to add skewness level and flexibility to the conventional Kumaraswamy distribution, these families of distribution have also led to the development of some generalizations of the Kumaraswamy distribution in the literature such as the transmuted Kumaraswamy distribution [24], the exponentiated Kumaraswamy distribution [25], the Kumaraswamy-Kumaraswamy distribution [26] and the Lomax-Kumaraswamy distribution [27].…”

Section: Introductionmentioning

confidence: 99%

“…The real life dataset: This dataset is on shape measurements of 48 rock samples from a petroleum reservoir. This data was extracted from BP research, image analysis by Ronit Katz, u Oxford and has been used for analysis [25]. The summary of the dataset is given in Table 2 as follows:…”

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confidence: 99%

Odd Lindley-Kumaraswamy Distribution: Model, Properties and Application

Kuje

Abubakar

Asongo

et al. 2020

JAMCS

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This article uses the odd Lindley-G family of distributions to propose and study a new compound distribution called “odd Lindley-Kumaraswamy distribution”. In this article, the density and distribution functions of the odd Lindley-Kumaraswamy distribution are defined and studied by deriving and discussing many properties of the distribution such as the ordinary moments, moment generating function, characteristics function, quantile function, reliability functions, order statistics and other useful measures. The unknown model parameters are also estimated by the method of maximum likelihood. The goodness-of-fit of the proposed distribution is demonstrated using two real life datasets. The results show that the proposed distribution outperforms the other fitted compound models selected for this study and hence it is a flexible generalization of the Kumaraswamy distribution.

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“…They obtained several mathematical properties of this class of distributions and discussed the two special cases: exp-Weibull and exp-beta distributions. Recently, Javanshiri et al (2013) introduced exp-uniform (EU) distribution by taking () Gx to be the cdf of the uniform distribution with parameters a and b and studied its properties and application.…”

Section: Introductionmentioning

confidence: 99%

A Generalized Gamma-Weibull Distribution: Model, Properties and Applications

Meshkat¹,

Torabi

Hamedani³

2016

Pak.j.stat.oper.res.

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We prepare a new method to generate family of distributions. Then, a family of univariate distributions generated by the Gamma random variable is defined. The generalized gamma-Weibull (GGW) distribution is studied as a special case of this family. Certain mathematical properties of moments are provided. To estimate the model parameters, the maximum likelihood estimators and the asymptotic distribution of the estimators are discussed. Certain characterizations of GGW distribution are presented. Finally, the usefulness of the new distribution, as well as its effectiveness in comparison with other distributions, are shown via an application of a real data set.

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Exp-Uniform Distribution: Properties and Characterizations

Cited by 6 publications

References 16 publications

Odd Lomax-Kumaraswamy Distribution: Its Properties and Applications

Odd Lomax-Kumaraswamy Distribution: Its Properties and Applications

Odd Lindley-Kumaraswamy Distribution: Model, Properties and Application

A Generalized Gamma-Weibull Distribution: Model, Properties and Applications

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