We develop a new continuous distribution called the beta-Burr type X distribution that extends the Burr type X distribution. The properties provide a comprehensive mathematical treatment of this distribution. Further more, various structural properties of the new distribution are derived, that includes moment generating function and the rth moment thus generalizing some results in the literature. We also obtain expressions for the density, moment generating function and rth moment of the order statistics. We consider the maximum likelihood estimation to estimate the parameters. Additionally, the asymptotic confidence intervals for the parameters are derived from the Fisher information matrix. Finally, simulation study is carried at under varying sample size to assess the performance of this model. Illustration the real dataset indicates that this new distribution can serve as a good alternative model to model positive real data in many areas.
Developing new compound distributions which are more flexible than the existing distributions have become the new trend in distribution theory. In this present study, the Lomax distribution was extended using the Gompertz family of distribution, its resulting densities and statistical properties were carefully derived, and the method of maximum likelihood estimation was proposed in estimating the model parameters. A simulation study to assess the performance of the parameters of Gompertz Lomax distribution was provided and an application to real life data was provided to assess the potentials of the newly derived distribution. Excerpt from the analysis indicates that the Gompertz Lomax distribution performed better than the Beta Lomax distribution, Weibull Lomax distribution, and Kumaraswamy Lomax distribution.
A new compound distribution called the Marshall-Olkin Inverse Lomax distribution (MO-ILD) was proposed, extending the inverse Lomax distribution by adding a new parameter to the existing distribution, leading to greater flexibility in modeling various data types. Its basic statistical properties were derived and model parameters estimated using the method of maximum likelihood. The Proposed distribution was applied to Cancer Stem Cell data and compared to the Marshall Olkin Flexible Weibull Extension Distribution (MO-FWED), and the Marshall-Olkin exponential Weibull distribution (MO-EWD). The Marshall-Olkin Inverse Lomax distribution provided a better fit than the Marshall Olkin Flexible Weibull Extension Distribution, and the Marshall-Olkin exponential Weibull distribution based on log-likelihood AIC, CAIC, BIC and HQIC values.
The Lomax distribution was extended in this paper using the Topp-Leone family of distributions. Some of its specific structural properties were established and the model parameters were estimated using maximum likelihood estimation method. The usefulness of the Topp-Leone Lomax distribution was demonstrated using an airbone communication transceiver dataset and comparison were made with respect to the Topp-Leone Burr XII, Topp-Leone Flexible Weibull and Lomax distributions. This is a preview of subscription content, access via your institution.
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