Abstract
In this work, the authors proposed a four parameter potentiated lifetime model named as Transmuted Exponentiated Moment Pareto (TEMP) distribution and discussed numerous characteristic measures of proposed model. Parameters are estimated by the method of maximum likelihood and performance of these estimates is also assessed by simulations study. Four suitable lifetime datasets are modeled by the TEMP distribution and the results support that the proposed model provides much better results as compared to its sub-models.
Highlights
An Italian Economist and civil engineer, Pareto (1848-1923) introduced the Power law
Four suitable lifetime datasets are modeled by the Transmuted Exponentiated Moment Pareto (TEMP) distribution and the results support that the proposed model provides much better results as compared to its sub-models
We introduce a four parameter distribution named as Transmuted Exponentiated Moment Pareto distribution (TEMP distribution) with CDF as
Summary
An Italian Economist and civil engineer, Pareto (1848-1923) introduced the Power law. Proposed and developed the exponentiated moment form of exponential distribution (EME) and discussed its various properties. Fatima and Roohi [12] developed a transmuted form of exponentiated Pareto-I distribution and discussed the increasing and decreasing behavior of hazard rate as well as derived some of its properties. Different mathematical properties and real time dataset are modeled by Kw-EFr. Shaw and Buckley [13] developed Quadratic Rank Transmutation Map (QRTM) to discover new family of non-Gaussian distributions. Merovci and Puka [14] proposed the transmuted form of Pareto distribution and discussed various properties along with its reliability behavior. Saboor et al [15] derived and studied the various structural properties and reliability measures of the transmuted form of exponential-Weibull distribution (TEW).
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