A new nonparametric quantile estimate for length-biased data with competing risks
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DOI: 10.1016/j.econlet.2015.10.023
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References listed on IDEAS
- L. Peng & J. P. Fine, 2007. "Nonparametric quantile inference with competing–risks data," Biometrika, Biometrika Trust, vol. 94(3), pages 735-744.
- Dauxois, Jean-Yves & Guilloux, Agathe, 2008. "Nonparametric inference under competing risks and selection-biased sampling," Journal of Multivariate Analysis, Elsevier, vol. 99(4), pages 589-605, April.
- Lancaster,Tony, 1992. "The Econometric Analysis of Transition Data," Cambridge Books, Cambridge University Press, number 9780521437899.
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Cited by:
- Shi, Jianhua & Ma, Huijuan & Zhou, Yong, 2018. "The nonparametric quantile estimation for length-biased and right-censored data," Statistics & Probability Letters, Elsevier, vol. 134(C), pages 150-158.
- Zhang, Feipeng & Yang, Jiejing & Ye, Min, 2020. "A nonparametric maximum likelihood estimation for biased-sampling data with zero-inflated truncation," Economics Letters, Elsevier, vol. 194(C).
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More about this item
Keywords
Competing risks; Quantile; EM algorithm; Length-biased data;All these keywords.
JEL classification:
- C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General
- C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
Statistics
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