Parameters Estimation Under Step-Stress Life Test Based on Censored Data From Generalized Exponential Model

This paper presents estimates of the parameters under step-stress partially accelerated life testing in the presence of censored data from generalized exponential distribution. The maximum likelihood procedure is used to derive point and asymptotic confidence interval estimations of the unknown parameters. Also, confidence bounds based on the log likelihood ratio are explored. The performance of the estimators is investigated numerically for different parameter values and different sample sizes in terms of their mean square error. A simulation study is made for illustrative purposes.