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Jackknife empirical likelihood confidence interval for the Gini index

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  • Wang, Dongliang
  • Zhao, Yichuan
  • Gilmore, Dirk W.

Abstract

Jackknife empirical likelihood for the Gini index is derived. Adjusted jackknife empirical likelihood and bootstrap calibration are further investigated. The resulting interval estimators are comparable to existing empirical likelihood methods in terms of coverage accuracy, but yield much shorter intervals.

Suggested Citation

  • Wang, Dongliang & Zhao, Yichuan & Gilmore, Dirk W., 2016. "Jackknife empirical likelihood confidence interval for the Gini index," Statistics & Probability Letters, Elsevier, vol. 110(C), pages 289-295.
    • Handle: RePEc:eee:stapro:v:110:y:2016:i:c:p:289-295
    DOI: 10.1016/j.spl.2015.09.026
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    2. Chen, Willa W. & Deo, Rohit S., 2018. "Subsampling based inference for U statistics under thick tails using self-normalization," Statistics & Probability Letters, Elsevier, vol. 138(C), pages 95-103.
    3. Yu, Xue & Zhao, Yichuan, 2019. "Empirical likelihood inference for semi-parametric transformation models with length-biased sampling," Computational Statistics & Data Analysis, Elsevier, vol. 132(C), pages 115-125.
    4. Encarnación Álvarez-Verdejo & Pablo J. Moya-Fernández & Juan F. Muñoz-Rosas, 2021. "Single Imputation Methods and Confidence Intervals for the Gini Index," Mathematics, MDPI, vol. 9(24), pages 1-20, December.
    5. Sudheesh K. Kattumannil & N. Sreelakshmi & N. Balakrishnan, 2022. "Non-Parametric Inference for Gini Covariance and its Variants," Sankhya A: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 84(2), pages 790-807, August.
    6. Kattumannil, Sudheesh K. & Dewan, Isha & N., Sreelaksmi, 2021. "Non-parametric estimation of Gini index with right censored observations," Statistics & Probability Letters, Elsevier, vol. 175(C).

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