Bias-correction for Weibull common shape estimation
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
Economic Theory | Statistical Methodology
Journal of Statistical Computation and Simulation
Taylor & Francis: STM, Behavioural Science and Public Health Titles
SHEN, Yan and YANG, Zhenlin.
Bias-correction for Weibull common shape estimation. (2015). Journal of Statistical Computation and Simulation. 85, (15), 3017-3046. Research Collection School Of Economics.
Available at: http://ink.library.smu.edu.sg/soe_research/1867