文摘
In this paper, a new censoring scheme, namely, adaptive Type-I progressively hybrid censoring scheme under a step-stress partially accelerated test model is introduced. It has some advantages over the progressively hybrid censoring schemes already discussed in the literature. Based on this censoring scheme, the maximum likelihood estimations of Weibull distribution parameters and the acceleration factor are considered. The biases and mean squared errors of the maximum likelihood estimators of the model parameters are computed to evaluate their performances in the presence of censoring scheme developed in this paper through a Monte Carlo simulation study. The results obtained under the adaptive Type-I progressively hybrid censoring scheme are compared with those produced under the non-adaptive Type-I progressively hybrid censoring scheme using three different progressive censoring schemes. Moreover, the confidence intervals lengths and their associated coverage probabilities are obtained for both adaptive and non-adaptive Type-I progressively hybrid censoring scheme. In addition, Optimum test plans are also developed to improve/guarantee the quality of the statistical inference.