Neutrosophic Generalized Exponential Distribution with Application

作     者：Rao, Gadde Srinivasa Norouzirad, Mina Mazarei, Danial 

作者机构：Department of Mathematics and Statistics The University of Dodoma PO. Box: 259 Dodoma Tanzania United Republic of Center for Mathematics and Application of Nova University Lisbon Lisbon Portugal Department of Statistics Faculty of Intelligent Systems Engineering and Data Science Persian Gulf University Bushehr Iran 

出 版 物：《Neutrosophic Sets and Systems》 (Neutrosophic Sets Syst.)

年 卷 期：2023年第55卷

页      面：471-485页

核心收录：

基　　金：distributions. This article develops a generalized exponential distribution inside a neutro-sophic statistical framework. The study of probability distributions based on neutrosophic statistics is quite uncommon. The generated neutrosophic generalization exponential distribution’s mathematical characteristics are investigated. The distribution’s nature is investigated using a variety of neutrosophic parametric combinations. The parameters are computed using the maximum likelihood approach. Simulation research is conducted in a neutrosophic setting. When expected  as the sample size grows  the average bias and MSE drop. The use of the suggested NGE distribution is then shown using actual data sets. Based on actual data sets  a comparison study with different distributions is also conducted. We draw the conclusion that the NGE distribution offers superior performance over current distributions based on studied instances. Funding: M. Norouzirad wishes to acknowledge funding provided by the National Funds through the FCT - Fundącão para a Ciência e a Tecnologia  I.P.  under the scope of the projects UIDB/00297/2020 and UIDP/00297/2020 (Center for Mathematics and Applications) 

主　　题：Maximum likelihood estimation 

摘      要：The objective of this article is to create a Neutrosophic Generalized Exponential (NGE) distribution in the presence of uncertainty. It is possible to calculate the mean, variance, moments, and reliability expression of the NGE distribution. With the help of graphs, the nature of the distribution and the reliability and hazard functions are studied. To determine the NGE distribution’s parameters, a maximum likelihood estimation technique is used. The performance of estimated parameters is further tested using simulations. Finally, an actual data set is examined to show how the NGE distribution works. According to a model validity test, the NGE distribution is superior to the existing neutrosophic distributions that can be found in the literature © 2023, Neutrosophic Sets and *** Rights Reserved.