Abstract
We provide a review on the empirical likelihood method for regression-type inference problems. The regression models considered in this review include parametric, semiparametric, and nonparametric models. Both missing data and censored data are accommodated.
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This invited paper is discussed in the comments available at: doi:10.1007/s11749-009-0160-z, doi:10.1007/s11749-009-0161-y, doi:10.1007/s11749-009-0162-x, doi:10.1007/s11749-009-0163-9, doi:10.1007/s11749-009-0164-8, doi:10.1007/s11749-009-0165-7.
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Chen, S.X., Van Keilegom, I. A review on empirical likelihood methods for regression. TEST 18, 415–447 (2009). https://doi.org/10.1007/s11749-009-0159-5
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DOI: https://doi.org/10.1007/s11749-009-0159-5
Keywords
- Censored data
- Empirical likelihood
- Missing data
- Nonparametric regression
- Parametric regression
- Semiparametric regression
- Wilks’ theorem