Application of Geometric Process for Generalized Exponential Distribution in Accelerated Life Testing with complete data [ ]


In this paper geometric process is used for the analysis of accelerated life testing under constant stress for the Generalized Exponential Distribution using complete data. By assuming that approach the lifetimes of units under increasing stress levels form a geometric process, the maximum likelihood estimation approached is used for the estimation of parameters. In order to get the asymptotic variance of the ML estimators, the Fisher information matrix is constructed. The asymptotic interval estimates of the parameters are then obtained by using this asymptotic variance. In the last, a simulation study is performed to illustrate the statistical properties of the parameters and the confidence intervals.