Generalized Mixtures of Exponential Distribution and Associated Inference

A new generalization of the exponential distribution, namely the generalized mixture of exponential distribution, is introduced. Some of its basic properties, such as hazard function, moments, order statistics, mean deviation, measures of uncertainly, and reliability probability, are studied. Three different estimation methods are investigated by the maximum likelihood estimator, least-square estimator, and weighted least-square estimator. The performances of the estimators are assessed by simulation studies. Real-world applications of the proposed distribution are explored, and data fitting results show that the new distribution performs better than its competitors.

Automated summary

A new generalized mixture of exponential distribution is introduced, with its basic properties and estimation methods studied. Simulation studies are conducted to assess the performance of the estimators. Real-world applications show that the new distribution outperforms its competitors.