Accelerated Life Tests of Series System with Masked Data Under Generalized Gamma Lifetime Distributions

• Main Authors: Yi-chun Chen, 陳奕君
• Other Authors: Tsai-hung Fan
• Format: Others
• Language: zh-TW
• Published: 2011
• Online Access: http://ndltd.ncl.edu.tw/handle/03699699964021807781

碩士 === 國立中央大學 === 統計研究所 === 99 === In this thesis, we consider masked lifetime data with different distributions under Type-I censoring scheme. For generalized gamma lifetime distribution, we discuss the constant stress accelerated life testing in which the location parameters of the generalized gamma lifetime distributions of the components is of a linear relationship with the stress variables.For exponential lifetime distribution, we discuss the step-stress accelerated life testing in which the mean life time of each component is a log-linear function of the levels of the stress variables. We utilize the likelihood ratio test to select the appropriate lifetime distribution. The maximum likelihood estimates via EM algorithm is developed for the model parameters with the aid of parametric bootstrap method to estimate the resulting standard errors when the data are masked. Simulation results show that in large samples using the generalized gamma distribution to fit data is more robust, but the calculation is more time-consuming. Conversely, if using the exponential distribution to fit the generalized gamma data, the results are not so accurate.