Imprecise Statistical Inference for Accelerated Life Testing Data: Imprecision Related to Log-Rank Test

Author(s):  
Abdullah A. H. Ahmadini ◽  
Frank P. A. Coolen
Metrika ◽  
2021 ◽  
Author(s):  
Frank P. A. Coolen ◽  
Abdullah A. H. Ahmadini ◽  
Tahani Coolen-Maturi

AbstractThis paper presents an imprecise predictive inference method for accelerated life testing. The method is largely nonparametric, with a basic parametric function to link different stress levels. The log-rank test is used to provide imprecision for the link function parameter, which in turn provides robustness in the resulting lower and upper survival functions for a future observation at the normal stress level. An application using data from the literature is presented, and simulations show the performance and robustness of the method. In case of model misspecification, robustness may be achieved at the price of large imprecision, which would emphasize the need for more data or further model assumptions.


2014 ◽  
Vol 63 (3) ◽  
pp. 764-780 ◽  
Author(s):  
Xiang Po Zhang ◽  
Jian Zhong Shang ◽  
Xun Chen ◽  
Chun Hua Zhang ◽  
Ya Shun Wang

2011 ◽  
Vol 383-390 ◽  
pp. 6969-6974
Author(s):  
Li Qin ◽  
An Li Shi

The model silicon pressure sensor was taken as the object; in this paper, we built failure physics equation of sensor under the vibration stress based on the failure modes and failure mechanism of pressure sensor, and using vibration stress as the acceleration factor to process accelerated life testing under invariableness stress. The results show that failure physics equation of sensor yields the inverse power law relationship. The estimated value of reliability character and accelerated life equation of sensor under the vibration stress was attained through analyzing testing data and the average life and reliable life of sensor has been attained through reliability evaluation.


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