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Using empirical likelihood methods to obtain range restricted weights in regression estimators for surveys

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Cited by:

  1. Denis Devaud & Yves Tillé, 2019. "Deville and Särndal’s calibration: revisiting a 25-years-old successful optimization problem," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 28(4), pages 1033-1065, December.
  2. Nicholas-James Clavet & Jean-Yves Duclos & Bernard Fortin & Steeve Marchand, 2012. "Le Québec, 2004-2030 : une analyse de micro-simulation," CIRANO Project Reports 2012rp-16, CIRANO.
  3. Peisong Han & Linglong Kong & Jiwei Zhao & Xingcai Zhou, 2019. "A general framework for quantile estimation with incomplete data," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 81(2), pages 305-333, April.
  4. Jan Pablo Burgard & Ralf Münnich & Martin Rupp, 2019. "A Generalized Calibration Approach Ensuring Coherent Estimates with Small Area Constraints," Research Papers in Economics 2019-10, University of Trier, Department of Economics.
  5. Han, Peisong & Song, Peter X.-K. & Wang, Lu, 2015. "Achieving semiparametric efficiency bound in longitudinal data analysis with dropouts," Journal of Multivariate Analysis, Elsevier, vol. 135(C), pages 59-70.
  6. Sanjay Chaudhuri & Malay Ghosh, 2011. "Empirical likelihood for small area estimation," Biometrika, Biometrika Trust, vol. 98(2), pages 473-480.
  7. Williams Matthew & Berg Emily, 2013. "Incorporating User Input Into Optimal Constraining Procedures for Survey Estimates," Journal of Official Statistics, Sciendo, vol. 29(3), pages 375-396, June.
  8. Denis Heng Yan Leung & Ken Yamada & Biao Zhang, 2015. "Enriching Surveys with Supplementary Data and its Application to Studying Wage Regression," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 42(1), pages 155-179, March.
  9. Jae Kwang Kim & Mingue Park, 2010. "Calibration Estimation in Survey Sampling," International Statistical Review, International Statistical Institute, vol. 78(1), pages 21-39, April.
  10. Peisong Han, 2014. "Multiply Robust Estimation in Regression Analysis With Missing Data," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 109(507), pages 1159-1173, September.
  11. Shixiao Zhang & Peisong Han & Changbao Wu, 2023. "Calibration Techniques Encompassing Survey Sampling, Missing Data Analysis and Causal Inference," International Statistical Review, International Statistical Institute, vol. 91(2), pages 165-192, August.
  12. Zhang, Yan-Qing & Tang, Nian-Sheng, 2017. "Bayesian local influence analysis of general estimating equations with nonignorable missing data," Computational Statistics & Data Analysis, Elsevier, vol. 105(C), pages 184-200.
  13. Rong Tang & Yun Yang, 2022. "Bayesian inference for risk minimization via exponentially tilted empirical likelihood," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 84(4), pages 1257-1286, September.
  14. Jean-Francois Beaumont & Cynthia Bocci, 2008. "Another look at ridge calibration," Metron - International Journal of Statistics, Dipartimento di Statistica, Probabilità e Statistiche Applicate - University of Rome, vol. 0(1), pages 5-20.
  15. Variyath A. M., 2013. "Empirical Likelihood Based Control Charts," Stochastics and Quality Control, De Gruyter, vol. 28(1), pages 37-44, October.
  16. Changbao Wu & Wilson W. Lu, 2016. "Calibration Weighting Methods for Complex Surveys," International Statistical Review, International Statistical Institute, vol. 84(1), pages 79-98, April.
  17. Yves G. Berger, 2016. "Empirical Likelihood Inference for the Rao-Hartley-Cochran Sampling Design," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 43(3), pages 721-735, September.
  18. Ying Sheng & Yifei Sun & Chiung‐Yu Huang & Mi‐Ok Kim, 2022. "Synthesizing external aggregated information in the presence of population heterogeneity: A penalized empirical likelihood approach," Biometrics, The International Biometric Society, vol. 78(2), pages 679-690, June.
  19. Jing Cheng & Dylan S. Small, 2021. "Semiparametric models and inference for the effect of a treatment when the outcome is nonnegative with clumping at zero," Biometrics, The International Biometric Society, vol. 77(4), pages 1187-1201, December.
  20. M. Rueda & J.F. Muñoz, 2009. "New Model‐assisted Estimators for the Distribution Function Using the Pseudo Empirical Likelihood Method," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 63(2), pages 227-244, May.
  21. Changbao Wu & Shixiao Zhang, 2019. "Comments on: Deville and Särndal’s calibration: revisiting a 25 years old successful optimization problem," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 28(4), pages 1082-1086, December.
  22. Jing Lv & Chaohui Guo & Jibo Wu, 2019. "Smoothed empirical likelihood inference via the modified Cholesky decomposition for quantile varying coefficient models with longitudinal data," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 28(3), pages 999-1032, September.
  23. Dong Liang & Genevieve Nesslage & Michael Wilberg & Thomas Miller, 2017. "Bayesian Calibration of Blue Crab (Callinectes sapidus) Abundance Indices Based on Probability Surveys," Journal of Agricultural, Biological and Environmental Statistics, Springer;The International Biometric Society;American Statistical Association, vol. 22(4), pages 481-497, December.
  24. Y. G. Berger & O. De La Riva Torres, 2016. "Empirical likelihood confidence intervals for complex sampling designs," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 78(2), pages 319-341, March.
  25. Oǧuz-Alper, Melike & Berger, Yves G., 2020. "Modelling multilevel data under complex sampling designs: An empirical likelihood approach," Computational Statistics & Data Analysis, Elsevier, vol. 145(C).
  26. Xiaogang Duan & Guosheng Yin, 2017. "Ensemble Approaches to Estimating the Population Mean with Missing Response," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 44(4), pages 899-917, December.
  27. 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.
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