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Improved Maximum Likelihood Estimation for the Weibull Distribution Under Length-Biased Sampling

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  • David E. Giles

    (University of Victoria)

Abstract

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.

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  • David E. Giles, 2021. "Improved Maximum Likelihood Estimation for the Weibull Distribution Under Length-Biased Sampling," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 19(1), pages 59-77, December.
    • Handle: RePEc:spr:jqecon:v:19:y:2021:i:1:d:10.1007_s40953-021-00263-x
    DOI: 10.1007/s40953-021-00263-x
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    References listed on IDEAS

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    6. Alessandro Nicita & Miho Shirotori & Bolormaa Tumurchudur Klok, 2013. "Survival Analysis Of The Exports Of Least Developed Countries: The Role Of Comparative Advantage," UNCTAD Blue Series Papers 54, United Nations Conference on Trade and Development.
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    Cited by:

    1. Yong Bao & Aman Ullah, 2021. "The Special Issue in Honor of Anirudh Lal Nagar: An Introduction," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 19(1), pages 1-8, December.

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