References
- Alemdjrodo, K., and Zhao, Y. (2019), ‘Reduce the Computation in Jackknife Empirical Likelihood for Comparing Two Correlated Gini Indices’, Journal of Nonparametric Statistics, 31(4), 849–866.
- Atkinson, A.B. (1970), ‘On the Measurement of Inequality’, Journal of Economic Theory, 2(3), 244–263.
- Bouadoumou, M., Zhao, Y., and Lu, Y. (2014), ‘Jackknife Empirical Likelihood for the Accelerated Failure Time Model with Censored Data’, Communications in Statistics – Simulation and Computation, 44(7), 1811–1832.
- Chen, S.X., and Cui, H. (2007), ‘On the Second-order Properties of Empirical Likelihood with Moment Restrictions’, Journal of Econometrics, 141(2), 492–516.
- Chen, S.X., and Keilegom, I.V. (2009), ‘A Review on Empirical Likelihood Methods for Regression’, Test, 18(3), 415–447.
- Chen, J., and Liu, Y. (2012), ‘Adjusted Empirical Likelihood with High-order One-sided Coverage Precision’, Statistics and Its Interface, 5(3), 281–292.
- Chen, J., Variyath, A., and Abraham, B. (2008), ‘Adjusted Empirical Likelihood and Its Properties’, Journal of Computational and Graphical Statistics, 17(2), 426–443.
- Cheng, Y., and Zhao, Y. (2019), ‘Bayesian Jackknife Empirical Likelihood’, Biometrika, 106(4), 981–988.
- Elteto, O., and Frigyes, E. (1968), ‘New Income Inequality Measures As Efficient Tools for Casual Analysis and Planning’, Econometrica: Journal of the Econometric Society, 36(2), 383–396.
- Emerson, S.C., and Owen, A.B. (2009), ‘Calibration of the Empirical Likelihood Method for a Vector Mean’, Electronic Journal of Statistics, 3, 1161–1192.
- Gastwirth, J.L. (1972), ‘The Estimation of the Lorenz Curve and Gini Index’, The Review of Economics and Statistics, 54, 3306–316.
- Gastwirth, J.L. (1974), ‘Large Sample Theory of Some Measures of Income Inequality’, Econometrica, 42(1), 191–196.
- Gong, Y., Peng, L., and Qi, Y. (2010), ‘Smoothed Jackknife Empirical Likelihood Method for ROC Curve’, Journal of Multivariate Analysis, 101(6), 1520–1531.
- Jing, B.Y., Tsao, M., and Zhou, W. (2017), ‘Transforming the Empirical Likelihood Towards Better Accuracy’, Canadian Journal of Statistics, 45(3), 340–352.
- Jing, B.Y., Yuan, J., and Zhou, W. (2009), ‘Jackknife Empirical Likelihood’, Journal of the American Statistical Association, 104(487), 1224–1232.
- Liang, W., Dai, H., and He, S. (2019), ‘Mean Empirical Likelihood’, Computational Statistics and Data Analysis, 138, 155–169.
- Liu, Y., and Chen, J. (2010), ‘Adjusted Empirical Likelihood with High-order Precision’, The Annals of Statistics, 38(3), 1341–1362.
- Liu, P., and Zhao, Y. (2023), ‘A Review of Recent Advances in Empirical Likelihood’, Wiley Interdisciplinary Reviews: Computational Statistics, 15(3), e1599.
- Marshall, A.W., Olkin, I., and Arnold, B.C. (1979), Inequalities: Theory of Majorization and Its Applications (Vol. 143), New York: Academic press.
- McDonald, J.B., and Jensen, B.C. (1979), ‘An Analysis of Some Properties of Alternative Measures of Income Inequality Based on the Gamma Distribution Function’, Journal of the American Statistical Association, 74(368), 856–860.
- Owen, A. (1988), ‘Empirical Likelihood Ratio Confidence Intervals for a Single Functional’, Biometrika, 75(2), 237–249.
- Owen, A. (1990), ‘Empirical Likelihood and Confidence Regions’, The Annals of Statistics, 18(1), 90–120.
- Owen, A. (1991), ‘Empirical Likelihood for Linear Models’, The Annals of Statistics, 19(1), 1725–1747.
- Owen, A. (2001), Empirical Likelihood, London: Chapman Hall/CRC.
- Quenouille, M. (1956), ‘Notes on Bias in Estimation’, Biometrika, 43(3/4), 353–360.
- Sang, Y., Dang, X., and Zhao, Y. (2021), ‘A Jackknife Empirical Likelihood Approach for K-sample Tests’, Canadian Journal of Statistics, 49(4), 1115–1135.
- Silverman, B. (1986), Density Estimation for Statistics and Data Analysis. Monographs on Statistics and Applied Probability, London: CRC.
- Sreelakshmi, N., Kattumannil, K., and Rituparna, S. (2019), ‘Jackknife Empirical Likelihood-based Inference for S-Gini Indices’, Communications in Statistics-Simulation and Computation, 50(6), 1645–1661.
- Thomas, D.R., and Grunkemeier, G.L. (1975), ‘Confidence Interval Estimation of Survival Probabilities for Censored Data’, Journal of the American Statistical Association, 70(352), 865–871.
- Tsao, M., and Wu, F. (2013), ‘Empirical Likelihood on the Full Parameter Space’, The Annals of Statistics, 41(4), 2176–2196.
- Tukey, J.W. (1958), ‘Bias and Confidence in Not Quite Large Samples’, Annals of Mathematical Statistics, 29(2), 614–623.
- Wang, L., Chen, J., and Pu, X. (2014), ‘Resampling Calibrated Adjusted Empirical Likelihood’, Canadian Journal of Statistics, 43(1), 42–59.
- Wang, R., Peng, L., and Qi, Y. (2013), ‘Jackknife Empirical Likelihood Test for Equality of Two High Dimensional Means’, Statistica Sinica, 23(2), 667–690.
- Wang, D., and Zhao, Y. (2016), ‘Jackknife Empirical Likelihood for Comparing Two Gini Indices’, Canadian Journal of Statistics, 44(1), 102–119.
- Zhao, Y., Meng, X., and Yang, H. (2015), ‘Jackknife Empirical Likelihood Inference for the Mean Absolute Deviation’, Computational Statistics and Data Analysis, 91, 92–101.
- Zhao, Y., Su, Y., and Yang, H. (2020), ‘Jackknife Empirical Likelihood Inference for the Pietra Ratio’, Computational Statistics and Data Analysis, 152, 107049.