An empirical likelihood approach to quantile regression with auxiliary information
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DOI: 10.1016/j.spl.2011.09.003
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Cited by:
- Muller, Ursula & Van Keilegom, Ingrid, 2013. "Efficient quantile regression with auxiliary information," LIDAM Discussion Papers ISBA 2013011, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
- Peixin Zhao & Xinrong Tang, 2016. "Imputation based statistical inference for partially linear quantile regression models with missing responses," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 79(8), pages 991-1009, November.
- 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.
- Xiaoshuang Zhou & Peixin Zhao & Yujie Gai, 2022. "Imputation-based empirical likelihood inferences for partially nonlinear quantile regression models with missing responses," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 106(4), pages 705-722, December.
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Keywords
Auxiliary information; Empirical likelihood; Estimating equations; Quantile regression;All these keywords.
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