Generalized Mixtures of Exponential Distribution and Associated Inference

Yaoting Yang, Weizhong Tian and Tingting Tong
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Yaoting Yang: Department of Applied Mathematics, Xi’an University of Technology, Xi'an 710054, China
Weizhong Tian: Department of Mathematical Sciences, Eastern New Mexico University, Portales, NM 88130, USA
Tingting Tong: Department of Mathematical Sciences, New Mexico State University, Las Cruces, NM 88003, USA

Mathematics, 2021, vol. 9, issue 12, 1-22

Abstract: 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.

Keywords: generalized mixture of exponential distribution; reliability probability; maximum likelihood estimator; weighted least-square estimator (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2021
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