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Rejoinder on: A review on empirical likelihood methods for regression

Citations

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Cited by:

  1. Chang, Jinyuan & Chen, Song Xi & Chen, Xiaohong, 2015. "High dimensional generalized empirical likelihood for moment restrictions with dependent data," Journal of Econometrics, Elsevier, vol. 185(1), pages 283-304.
  2. Yongsong Qin & Qingzhu Lei, 2021. "Empirical Likelihood for Mixed Regressive, Spatial Autoregressive Model Based on GMM," Sankhya A: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 83(1), pages 353-378, February.
  3. Hong Guo & Changliang Zou & Zhaojun Wang & Bin Chen, 2014. "Empirical likelihood for high-dimensional linear regression models," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 77(7), pages 921-945, October.
  4. Karun Adusumilli & Taisuke Otsu, 2017. "Empirical Likelihood for Random Sets," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 112(519), pages 1064-1075, July.
  5. Huang, Zhensheng & Pang, Zhen & Zhang, Riquan, 2013. "Adaptive profile-empirical-likelihood inferences for generalized single-index models," Computational Statistics & Data Analysis, Elsevier, vol. 62(C), pages 70-82.
  6. Marco Cattaneo & Andrea Wiencierz, 2014. "On the implementation of LIR: the case of simple linear regression with interval data," Computational Statistics, Springer, vol. 29(3), pages 743-767, June.
  7. Otsu, Taisuke & Xu, Ke-Li & Matsushita, Yukitoshi, 2015. "Empirical likelihood for regression discontinuity design," Journal of Econometrics, Elsevier, vol. 186(1), pages 94-112.
  8. Bravo, Francesco & Escanciano, Juan Carlos & Van Keilegom, Ingrid, 2015. "Wilks' Phenomenon in Two-Step Semiparametric Empirical Likelihood Inference," LIDAM Discussion Papers ISBA 2015016, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
  9. Siddharta Chib & Minchul Shin & Anna Simoni, 2016. "Bayesian Empirical Likelihood Estimation and Comparison of Moment Condition Models," Working Papers 2016-21, Center for Research in Economics and Statistics.
  10. Zhong, Ping-Shou & Chen, Sixia, 2014. "Jackknife empirical likelihood inference with regression imputation and survey data," Journal of Multivariate Analysis, Elsevier, vol. 129(C), pages 193-205.
  11. Zhao, Yichuan & Su, Yueju & Yang, Hanfang, 2020. "Jackknife empirical likelihood inference for the Pietra ratio," Computational Statistics & Data Analysis, Elsevier, vol. 152(C).
  12. Zhang, Jia & Shi, Haoming & Tian, Lemeng & Xiao, Fengjun, 2019. "Penalized generalized empirical likelihood in high-dimensional weakly dependent data," Journal of Multivariate Analysis, Elsevier, vol. 171(C), pages 270-283.
  13. Tong Tong Wu & Gang Li & Chengyong Tang, 2015. "Empirical Likelihood for Censored Linear Regression and Variable Selection," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 42(3), pages 798-812, September.
  14. Yves G. Berger, 2020. "An empirical likelihood approach under cluster sampling with missing observations," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 72(1), pages 91-121, February.
  15. Roberto Baragona & Francesco Battaglia & Domenico Cucina, 2017. "Empirical likelihood ratio in penalty form and the convex hull problem," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 26(4), pages 507-529, November.
  16. Qinqin Hu & Lu Lin, 2017. "Conditional sure independence screening by conditional marginal empirical likelihood," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 69(1), pages 63-96, February.
  17. Jose Blanchet & Yang Kang, 2021. "Sample Out-of-Sample Inference Based on Wasserstein Distance," Operations Research, INFORMS, vol. 69(3), pages 985-1013, May.
  18. Weihua Zhao & Riquan Zhang & Yukun Liu & Jicai Liu, 2015. "Empirical likelihood based modal regression," Statistical Papers, Springer, vol. 56(2), pages 411-430, May.
  19. Zang, Yangguang & Zhang, Sanguo & Li, Qizhai & Zhang, Qingzhao, 2016. "Jackknife empirical likelihood test for high-dimensional regression coefficients," Computational Statistics & Data Analysis, Elsevier, vol. 94(C), pages 302-316.
  20. Yu Shen & Han-Ying Liang, 2018. "Quantile regression and its empirical likelihood with missing response at random," Statistical Papers, Springer, vol. 59(2), pages 685-707, June.
  21. Yongsong Qin, 2021. "Empirical Likelihood for Spatial Autoregressive Models with Spatial Autoregressive Disturbances," Sankhya A: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 83(1), pages 1-25, February.
  22. Julia Polak & Maxwell L. King & Xibin Zhang, 2014. "A Model Validation Procedure," Monash Econometrics and Business Statistics Working Papers 21/14, Monash University, Department of Econometrics and Business Statistics.
  23. Daniela Marella & Danny Pfeffermann, 2023. "Accounting for Non‐ignorable Sampling and Non‐response in Statistical Matching," International Statistical Review, International Statistical Institute, vol. 91(2), pages 269-293, August.
  24. Ngai Chan & Liang Peng & Rongmao Zhang, 2012. "Interval estimation of the tail index of a GARCH(1,1) model," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 21(3), pages 546-565, September.
  25. repec:cep:stiecm:/2014/574 is not listed on IDEAS
  26. Jin, Fei & Lee, Lung-fei, 2019. "GEL estimation and tests of spatial autoregressive models," Journal of Econometrics, Elsevier, vol. 208(2), pages 585-612.
  27. Li, Minqiang & Peng, Liang & Qi, Yongcheng, 2011. "Reduce computation in profile empirical likelihood method," MPRA Paper 33744, University Library of Munich, Germany.
  28. Sanjay Chaudhuri & Debashis Mondal & Teng Yin, 2017. "Hamiltonian Monte Carlo sampling in Bayesian empirical likelihood computation," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 79(1), pages 293-320, January.
  29. Zhouping Li & Yuanyuan Lin & Guoliang Zhou & Wang Zhou, 2014. "Empirical likelihood for least absolute relative error regression," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 23(1), pages 86-99, March.
  30. Jingjing Qu & Hon Keung Tony Ng & Chul Moon, 2024. "Empirical likelihood ratio tests for homogeneity of component lifetime distributions based on system lifetime data," Computational Statistics, Springer, vol. 39(6), pages 3007-3029, September.
  31. Yves G. Berger & Ewa Kabzińska, 2020. "Empirical Likelihood Approach for Aligning Information from Multiple Surveys," International Statistical Review, International Statistical Institute, vol. 88(1), pages 54-74, April.
  32. Hui-Ling Lin & Zhouping Li & Dongliang Wang & Yichuan Zhao, 2017. "Jackknife empirical likelihood for the error variance in linear models," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 29(2), pages 151-166, April.
  33. Berger, Yves G. & Patilea, Valentin, 2022. "A semi-parametric empirical likelihood approach for conditional estimating equations under endogenous selection," Econometrics and Statistics, Elsevier, vol. 24(C), pages 151-163.
  34. Zhang, Rongmao & Peng, Liang & Qi, Yongcheng, 2012. "Jackknife-blockwise empirical likelihood methods under dependence," Journal of Multivariate Analysis, Elsevier, vol. 104(1), pages 56-72, February.
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