Affiliation:
1. Department of Quantitative Health Sciences, Cleveland Clinic, Ohio
2. Department of Mathematics and Statistics, Ahmadu Bello University, Kaduna State, Nigeria
Abstract
In this work, a new family of distribution, which generalizes the Beta Weibull-G family by the introduction of a shape parameter to enhance better fit and flexibility, called the Modified Beta Weibull-G family of distributions is obtained. The mixture representation of the derived family of distributions was discussed, with the results effective in studying moments, moment generating functions, order statistics. Parameters of the family of distributions were estimated using the maximum likelihood estimation method. By utilizing this modified class of distributions, we build a new distribution called the modified beta Weibull Weibull and applied it to engineering datasets. Application revealed a better performance in model fit, compared to some other distributions.
Subject
Artificial Intelligence,General Engineering,Statistics and Probability
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