Improved likelihood inferences for Weibull regression model

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

MATHEMATICS SUBJECT CLASSIFCATION:

• 62N02
• 62N05
• 62N86

Acknowledgements

We are grateful to the Editor, Professor Richard Krutchkoff, an Associate Editor and two anonymous referees for the helpful comments that have led to significant improvements in the paper.

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

This work was supported by the National Natural Science Foundation of China [grant number 71401146], and by MOE (Ministry of Education) Key Laboratory of Econometrics and Fujian Key Laboratory of Statistical Sciences, China.