The novel Kumaraswamy power Frechet distribution with data analysis related to diverse scientific areas

Alsadat, Najwan; Ahmad, Aijaz; Jallal, Muzamil; Gemeay, Ahmed M.; Meraou, Mohammed Amine; Hussam, Eslam; M.Elmetwally, Ehab

doi:10.1016/j.aej.2023.03.003

Cited by 10 publications

(3 citation statements)

References 29 publications

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“…The values for the monthly maximum snowfall data set. [5], Wani and Shafi [30], Alsadat [25] and Alsadat et al [26]. The considered data is given as…”

Section: Maximum Product Of Spacingsmentioning

confidence: 99%

On the Analysis of Environmental and Engineering Data Using Alpha Power Transformed Cosine Moment Exponential Model

Alrweili

2024

Int. J. Anal. Appl.

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This article introduces a new model using the alpha power cosine transformed method for modeling complex data used in hydrology and engineering studies. The alpha power novel distribution transformed the cosine moment exponential model with two parameters. Its probability density function can be skewed and unimodal. Various statistical and mathematical properties are established, and the unknown parameters of the suggested model are determined using numerous estimation procedures. Also, the potential of these estimation techniques is calculated via some simulation studies. In the end, two real data sets are made using the proposed model to make a practical application in environmental and survival fields. The potential and utility of the recommended distribution are verified with other well known models and it shows great superiority in fitting the proposed data sets.

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“…The values for the monthly maximum snowfall data set. [5], Wani and Shafi [30], Alsadat [25] and Alsadat et al [26]. The considered data is given as…”

Section: Maximum Product Of Spacingsmentioning

confidence: 99%

On the Analysis of Environmental and Engineering Data Using Alpha Power Transformed Cosine Moment Exponential Model

Alrweili

2024

Int. J. Anal. Appl.

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“…Bell generalized FPD was introduced by [59]. Bell Weibull (BellW), a unique model of this family, was first introduced.…”

Section: Literature Reviewmentioning

confidence: 99%

A Novel Odd Beta Prime-Logistic Distribution: Desirable Mathematical Properties and Applications to Engineering and Environmental Data

et al. 2023

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In parametric statistical modeling, it is important to construct new extensions of existing probability distributions (PDs) that can make modeling data more flexible and help stakeholders make better decisions. In the present study, a new family of probability distributions (FPDs) called the odd beta prime generalized (OBP-G) FPDs is proposed to improve the traditional PDs. A new PD called the odd beta prime-logistic (OBP-logistic) distribution has been developed based on the developed OBP-G FPDs. Some desirable mathematical properties of the proposed OBP-logistic distribution, including the moments, moment-generating function, information-generating function, quantile function, stress–strength, order statistics, and entropies, are studied and derived. The proposed OBP-logistic distribution’s parameters are determined by adopting the maximum likelihood estimation (MLE) method. The applicability of the new PD was demonstrated by employing three data sets and these were compared by the known extended logistic distributions, such as the gamma generalized logistic distribution, new modified exponential logistic distribution, gamma-logistic distribution, exponential modified Weibull logistic distribution, exponentiated Weibull logistic distribution, and transmuted Weibull logistic distribution. The findings reveal that the studied distribution provides better results than the competing PDs. The empirical results showed that the new OBP-logistic distribution performs better than the other PDs based on several statistical metrics. We hoped that the newly constructed OBP-logistic distribution would be an alternative to other well-known extended logistic distributions for the statistical modeling of symmetric and skewed data sets.

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“…The literature on distribution theory contains a series of probability distributions for analyzing and predicting real phenomena in various applied areas, such as the healthcare and biomedical sectors, engineering sector, actuarial and management sciences, education, and hydrology [1][2][3][4][5][6][7][8]. However, no particular probability model is appropriate for analyzing and predicting every phenomenon.…”

Section: Introductionmentioning

confidence: 99%

A Weighted Cosine-G Family of Distributions: Properties and Illustration Using Time-to-Event Data

Odhah,

Alshanbari,

Ahmad

et al. 2023

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Modeling and predicting time-to-event phenomena in engineering, sports, and medical sectors are very crucial. Numerous models have been proposed for modeling such types of data sets. These models are introduced by adding one or more parameters to the traditional distributions. The addition of new parameters to the traditional distributions leads to serious issues, such as estimation consequences and re-parametrization problems. To avoid such problems, this paper introduces a new method for generating new probability distributions without any additional parameters. The proposed method may be called a weighted cosine-G family of distributions. Different distributional properties of the weighted cosine-G family, along with the maximum likelihood estimators, are obtained. A special model of the weighted cosine-G family, by utilizing the Weibull model, is considered. The special model of the weighted cosine-G family may be called a weighted cosine-Weibull distribution. A simulation study of the weighted cosine-Weibull model is conducted to evaluate the performances of its estimators. Finally, the applications of the weighted cosine-Weibull distribution are shown by considering three data sets related to the time-to-event phenomena.

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The novel Kumaraswamy power Frechet distribution with data analysis related to diverse scientific areas

Cited by 10 publications

References 29 publications

On the Analysis of Environmental and Engineering Data Using Alpha Power Transformed Cosine Moment Exponential Model

On the Analysis of Environmental and Engineering Data Using Alpha Power Transformed Cosine Moment Exponential Model

A Novel Odd Beta Prime-Logistic Distribution: Desirable Mathematical Properties and Applications to Engineering and Environmental Data

A Weighted Cosine-G Family of Distributions: Properties and Illustration Using Time-to-Event Data

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