Selecting the best geometric distribution based on type-I censored data: a Bayesian approach |
| |
Authors: | Lee-Shen Chen |
| |
Institution: | Department of Applied Statistics and Information Science, Ming Chuan University, Taoyuan, Taiwan |
| |
Abstract: | This paper considers the statistical reliability on discrete failure data and the selection of the best geometric distribution having the smallest failure probability from among several competitors. Using the Bayesian approach a Bayes selection rule based on type-I censored data is derived and its associated monotonicity is also obtained. An early selection rule which allows us to make a selection possible earlier than the censoring time of the life testing experiment is proposed. This early selection rule can be shown to be equivalent to the Bayes selection rule. An illustrative example is given to demonstrate the use and the performance of the early selection rule. |
| |
Keywords: | Bayes selection rule Best population Early selection rule Life testing Type-I censoring |
本文献已被 ScienceDirect 等数据库收录! |