Statistical Analysis Based on Adaptive Progressive Hybrid Censored Sample From Alpha Power Generalized Exponential Distribution

For the alpha power generalized exponential model, the maximum likelihood and Bayes estimations of unknown distribution parameters are discussed under an adaptive Type-II progressive hybrid censored sample. The confidence intervals of the distribution parameters are calculated approximately, and further employ the delta method to obtain approximate interval estimations of the associated survival function and hazard function. The Bayes estimates and the credible intervals of these quantities are also obtained. The results of simulation and analysis of an actual life data set are used to evaluate the performance the proposed method and illustrate its application possibility.