We consider the estimation of the parameters of the Weibull distribution when the data arise from "length-biased" sampling. Specifically, the appropriate weighted density is formulated and we analyze the finite-sample properties of the maximum likelihood estimators for its parameters. The analytic Cox-Snell "corrective" approach is used to reduce the biases of these estimators, and we find that this can be done effectively and without detrimental consequences for the mean squared errors. Bootstrap bias-correction is also found to be effective. Simulation results also illustrate the severe consequences of failing to allow for "length-biased" sampling, even in very large samples.
机构:
Emory Univ, Dept Biostat & Bioinformat, Atlanta, GA 30322 USAEmory Univ, Dept Biostat & Bioinformat, Atlanta, GA 30322 USA
Ma, Huijuan
Zhou, Yong
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Shanghai Univ Finance & Econ, Sch Stat & Management, Shanghai, Peoples R China
Chinese Acad Sci, Acad Math & Syst Sci, Beijing, Peoples R ChinaEmory Univ, Dept Biostat & Bioinformat, Atlanta, GA 30322 USA
机构:
Chinese Acad Sci, Acad Math & Syst Sci, Beijing 100190, Peoples R ChinaChinese Acad Sci, Acad Math & Syst Sci, Beijing 100190, Peoples R China
Wang, Xuan
Wang, Qihua
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Chinese Acad Sci, Acad Math & Syst Sci, Beijing 100190, Peoples R China
Shenzhen Univ, Inst Stat Sci, Shenzhen 518006, Peoples R ChinaChinese Acad Sci, Acad Math & Syst Sci, Beijing 100190, Peoples R China
机构:
Department of Mathematics, Mirpur University of Science and Technology (MUST), MirpurDepartment of Mathematics, Mirpur University of Science and Technology (MUST), Mirpur
Khadim A.
Lin Z.
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Department of Mathematics, Institute of Statistics, Zhejiang University, HangzhouDepartment of Mathematics, Mirpur University of Science and Technology (MUST), Mirpur