Improved likelihood inferences for Weibull regression model. Issue 12 (13th August 2017) - Shen, Yan; Yang, Zhenlin
ABSTRACT: 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.