Bias-correction for Weibull Common Shape Estimation

• Main Authors: SHEN, Yan, YANG, Zhenlin
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2015
• Subjects: Bias correction; Bootstrap; Right censoring; Stochastic expansion; Weibull models; Econometrics
• Online Access: https://ink.library.smu.edu.sg/soe_research/1574; https://ink.library.smu.edu.sg/context/soe_research/article/2573/viewcontent/ShenYang_JSCS2014f.pdf
• Institution: Singapore Management University

A general method for correcting the bias of the maximum likelihood estimator (MLE) of the common shape parameter of Weibull populations, allowing a general right censorship, is proposed in this paper. Extensive simulation results show that the new method is very effective in correcting the bias of the MLE, regardless of censoring mechanism, sample size, censoring proportion and number of populations involved. The method can be extended to more complicated Weibull models.