Life data frequently arise in many reliability studies, such as accelerated life tests studies. This paper considers the part of life data where failure and censoring observations may exist. To develop statistical methods and theory for the analysis of these data, a new approach was proposed to obtain the exact lower and upper confidence limits for the mean life of the exponential distribution with Type-I censoring data. It is assumed that the acceleration factor is a random variable, and that the distribution of the acceleration factor is known from some empirical information or the meta analysis. A method for constructing the lower and upper confidence limits for the parameter based on an ordering relation among the sample space was proposed. Simulation studies and analyses of two examples suggest that the proposed method performed well.

寿命数据经常出现在许多可靠性研究中，例如加速寿命测试研究。本文考虑了生命数据中可能存在故障和检查结果的部分。为了发展用于分析这些数据的统计方法和理论，提出了一种新的方法来获取具有I型检查数据的指数分布的平均寿命的确切上下限。假设加速度因子是一个随机变量，并且可以从一些经验信息或元分析中获知加速度因子的分布。提出了一种基于样本空间之间的排序关系构造参数的上下置信限的方法。仿真研究和两个例子的分析表明，该方法性能良好。