A general procedure is developed for bias-correcting the maximum likelihood estimators (MLEs) of the parameters of Weibull regression model with either complete or right-censored data. Following the bias correction, variance corrections and hence improved t-ratios for model parameters are presented. Potentially improved t-ratios for other reliability-related quantities are also discussed. Simulation results show that the proposed method is effective in correcting the bias of the MLEs, and the resulted t-ratios generally improve over the regular t-ratios.
Bias correction, variance correction, bootstrap, improved t-ratios, stochastic expansion, right censoring
Journal of Statistical Computation and Simulation
Taylor & Francis: STM, Behavioural Science and Public Health Titles
SHEN, Yan and YANG, Zhenlin.
Improved likelihood inferences for Weibull regression model. (2017). Journal of Statistical Computation and Simulation. 87, (12), 2349-2371. Research Collection School Of Economics.
Available at: http://ink.library.smu.edu.sg/soe_research/2080
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