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Improved likelihood inferences for Weibull regression model
Authors:Yan Shen  Zhenlin Yang
Institution:1. Department of Statistics, School of Economics, Xiamen University, Xiamen, Fujian, People's Republic of Chinasheny@xmu.edu.cn;3. School of Economics, Singapore Management University, Singapore
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.
Keywords:Bias correction  variance correction  bootstrap  improved t-ratios  stochastic expansion  right censoring
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