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.
Bias correction, Bootstrap, Right censoring, Stochastic expansion, Weibull models
Journal of Statistical Computation and Simulation
Shen, Y. and YANG, Zhenlin.
Bias-correction for Weibull Common Shape Estimation. (2013). Journal of Statistical Computation and Simulation. Research Collection School Of Economics.
Available at: http://ink.library.smu.edu.sg/soe_research/1574
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