Improved likelihood inferences for Weibull regression model

Yan Shen, Zhenlin Yang
2017 Journal of Statistical Computation and Simulation  
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
more » ... sulted t-ratios generally improve over the regular t-ratios.
doi:10.1080/00949655.2017.1331441 fatcat:x7ehfqko4bg4na6sew542c47w4