Affiliations: [1] School of Business Administration, Southwestern University of Finance and Economics, No. 555, Liutai Ave, Wenjiang Zone, Chengdu 611130, China | [2] Yangtze Normal University, No. 98, Julong Ave, Fuling Zone, Chongqing, 408100, China | [3] School of Management and Economics, University of Electronic Science and Technology of China, No. 2006, Xiyuan Ave, West Hi-Tech Zone, Chengdu 611731, China, e-mail: [email protected], [email protected], [email protected], [email protected], [email protected]
Correspondence:
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Corresponding author.
Abstract: This paper presents minimum mean square error (MMSE) estimators for mean life and failure rate of Exponential distribution model based on failure censored step-stress accelerated life-testing (SSALT) data. The MMSE estimators are drived by revising the corresponding unbiased estimators in terms of mean square error (MSE). Two theorems prove mathematically the fact that MSE of the resulting MMSE estimators are smaller than that of the corresponding unbiased estimators. The results show that the MMSE estimators are more efficient than the unbiased estimators and maximum likelihood estimators (MLEs) in small and moderate sample size.
Keywords: Step-stress accelerated life-testing (SSALT), exponential distribution, mean life, failure rate, mean square error (MSE)
Journal: Informatica, vol. 27, no. 4, pp. 755-765, 2016
