时间：10月15日下午2:30 - 3:30

地点：舜德楼北510会议室

报告人：Associate Professor Guo-Liang Tian, PhD (Dept of Statistics and Actuarial Science, The University of Hong Kong)

报告题目：Predictive Analyses for a Reliability Growth Model Using Bayesian Approach

报告摘要：

Nonhomogeneous Poisson process (NHPP) also known as Weibull process with power law, has been widely used in modeling hardware reliability growth and detecting software failures. Although statistical inferences on the Weibull process have been studied extensively by various authors, relevant discussions on predictive analysis are scattered in the literature. It is well known that the predictive analysis is very useful for determining when to terminate the development testing process. This talk presents some results about predictive analyses for Weibull processes. Motivated by the demand on developing complex high-cost and high-reliability systems (e.g., weapon systems, aircraft generators, jet engines), we address several issues in single-sample and two-sample prediction associated closely with development testing program. Bayesian approaches based on non-informative prior are adopted to develop explicit solutions to these problems. We will apply our methodologies to two real examples from a radar system development and an electronics system development.

欢迎感兴趣的师生准时参加。