A New Generalized Gamma-Weibull Distribution and Its Applications

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dc.contributor.authorNihimat I. Aleshinloye
dc.contributor.authorSamuel A. Aderoju
dc.contributor.authorAlfred A. Abiodun
dc.contributor.authorBako L. Taiwo
dc.date.accessioned2023-06-07T13:01:09Z
dc.date.available2023-06-07T13:01:09Z
dc.date.issued2023-03-10
dc.description.abstractIn this paper, a New Generalized Gamma-Weibull (NGGW) distribution is developed by compounding Weibull and generalized gamma distribution. Some mathematical properties such as moments, R enyi entropy and order statistics are derived and discussed. The maximum likelihood estimation (MLE) method is used to estimate the model parameters. The proposed model is applied to two real-life datasets to illustrate its performance and flexibility as compared to some other competing distributions. The results obtained show that the new distribution fits each of the data better than the other competing distributions.
dc.identifier.issnhttps://doi.org/10.55810/2313-0083.1021
dc.identifier.urihttps://kwasuspace.kwasu.edu.ng/handle/123456789/143
dc.language.isoen
dc.publisherAL-BAHIR JOURNAL FOR ENGINEERING AND PURE SCIENCES
dc.titleA New Generalized Gamma-Weibull Distribution and Its Applications
dc.typeArticle
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