Bayesian and non-Bayesian estimation for the multiple-stress model under progressively type-Ⅱ hybrid censoring with optimal design

In this paper, estimation of the accelerated life testing (ALT) for the stress model in multiple case is considered. Maximum likelihood estimation is employed to obtain the estimated parameters of the multiple-stress model by a maximum likelihood approach. A Bayesian estimation procedure is proposed to estimate the parameters of the multiple-stress model. Estimation methods are considered under a progressively type-Ⅱ hybrid censoring scheme with generalized inverted exponential distribution. Different criteria are discussed to determine the optimal design of the progressively type-Ⅱ hybrid censoring scheme for the multiple-stress model. A simulation study is conducted to obtain results for the maximum likelihood and Bayesian estimates of the parameters of the multiple-stress model. Real data application involving the breakdown voltage of insulating oil is introduced to analyze the performance of the multiple-stress model under progressively type-Ⅱ hybrid censoring scheme with generalized inverted exponential distribution.