Bias-correction for Weibull Common Shape Estimation

Bias-correction for Weibull Common Shape Estimation

A general method for correcting the bias of the maximum likelihood estimator (MLE) of the common shape parameter of Weibull populations, allowing a general right censorship, is proposed in this paper. Extensive simulation results show that the new method is very effective in correcting the bias of th...

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Bibliographic Details
Main Authors: SHEN, Yan, YANG, Zhenlin
Format: text
Language:English
Published: Institutional Knowledge at Singapore Management University 2015
Subjects:
Bias correction
Bootstrap
Right censoring
Stochastic expansion
Weibull models
Econometrics
Online Access:https://ink.library.smu.edu.sg/soe_research/1574
https://ink.library.smu.edu.sg/context/soe_research/article/2573/viewcontent/ShenYang_JSCS2014f.pdf
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Institution: Singapore Management University
Language: English
Description
Summary:A general method for correcting the bias of the maximum likelihood estimator (MLE) of the common shape parameter of Weibull populations, allowing a general right censorship, is proposed in this paper. Extensive simulation results show that the new method is very effective in correcting the bias of the MLE, regardless of censoring mechanism, sample size, censoring proportion and number of populations involved. The method can be extended to more complicated Weibull models.

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