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A review on empirical likelihood methods for regression

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  • Song Chen

    ()

  • Ingrid Van Keilegom

    ()

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File URL: http://hdl.handle.net/10.1007/s11749-009-0159-5
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Bibliographic Info

Article provided by Springer in its journal TEST.

Volume (Year): 18 (2009)
Issue (Month): 3 (November)
Pages: 415-447

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Handle: RePEc:spr:testjl:v:18:y:2009:i:3:p:415-447

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Related research

Keywords: Censored data; Empirical likelihood; Missing data; Nonparametric regression; Parametric regression; Semiparametric regression; Wilks’ theorem; 62-02; 62E20; 62F03; 62G08; 62G10; 62J02; 62N01;

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References

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  1. Xue, Liu-Gen & Zhu, Lixing, 2006. "Empirical likelihood for single-index models," Journal of Multivariate Analysis, Elsevier, vol. 97(6), pages 1295-1312, July.
  2. Elisa M. Molanes Lopez & Ingrid Van Keilegom & No�L Veraverbeke, 2009. "Empirical Likelihood for Non-Smooth Criterion Functions," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 36(3), pages 413-432.
  3. Shi, Jian & Lau, Tai-Shing, 2000. "Empirical Likelihood for Partially Linear Models," Journal of Multivariate Analysis, Elsevier, vol. 72(1), pages 132-148, January.
  4. Gengsheng Qin, 2001. "Empirical Likelihood for Censored Linear Regression," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 28(4), pages 661-673.
  5. Song Xi Chen & Hengjian Cui, 2006. "On Bartlett correction of empirical likelihood in the presence of nuisance parameters," Biometrika, Biometrika Trust, Biometrika Trust, vol. 93(1), pages 215-220, March.
  6. Qi-Hua Wang & Bing-Yi Jing, 2003. "Empirical likelihood for partial linear models," Annals of the Institute of Statistical Mathematics, Springer, vol. 55(3), pages 585-595, September.
  7. Hu, Xuemei & Wang, Zhizhong & Zhao, Zhiwei, 2009. "Empirical likelihood for semiparametric varying-coefficient partially linear errors-in-variables models," Statistics & Probability Letters, Elsevier, vol. 79(8), pages 1044-1052, April.
  8. Chen S.X. & Leung D.H.Y. & Qin J., 2003. "Information Recovery in a Study With Surrogate Endpoints," Journal of the American Statistical Association, American Statistical Association, American Statistical Association, vol. 98, pages 1052-1062, January.
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Cited by:
  1. 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, Springer, vol. 23(1), pages 86-99, March.
  2. Karun Adusumilli & Taisuke Otsu, 2014. "Empirical Likelihood for Random Sets," STICERD - Econometrics Paper Series /2014/574, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
  3. 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.
  4. 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, Springer, vol. 21(3), pages 546-565, September.
  5. Li, Minqiang & Peng, Liang & Qi, Yongcheng, 2011. "Reduce computation in profile empirical likelihood method," MPRA Paper 33744, University Library of Munich, Germany.
  6. 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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