Exact Confidence Limits for the Parameter of an Exponential Distribution in the Accelerated Life Tests under Type-I Censoring

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.