LI ZhongGui, HE ShuYuan. Smoothed Empirical Likelihood Inference for Quantile Regression[J]. Chinese Journal of Applied Probability and Statistics, 2017, 33(5): 497-507. DOI: 10.3969/j.issn.1001-4268.2017.05.006
Citation:
LI ZhongGui, HE ShuYuan. Smoothed Empirical Likelihood Inference for Quantile Regression[J]. Chinese Journal of Applied Probability and Statistics, 2017, 33(5): 497-507. DOI: 10.3969/j.issn.1001-4268.2017.05.006
LI ZhongGui, HE ShuYuan. Smoothed Empirical Likelihood Inference for Quantile Regression[J]. Chinese Journal of Applied Probability and Statistics, 2017, 33(5): 497-507. DOI: 10.3969/j.issn.1001-4268.2017.05.006
Citation:
LI ZhongGui, HE ShuYuan. Smoothed Empirical Likelihood Inference for Quantile Regression[J]. Chinese Journal of Applied Probability and Statistics, 2017, 33(5): 497-507. DOI: 10.3969/j.issn.1001-4268.2017.05.006
Smoothed Empirical Likelihood Inference for Quantile Regression
For linear quantile regression model, this paper proves that the test statistics, besed on smoothed empirical likelihood (SEL) method and least absolute deviation (LAD) method, both converge weakly to a noncentral Chi-square distribution under the local alternatives H_1:\beta=\beta_0+a_n, where \beta is the true parameter. Simulation results show that the SEL method is more efficient than the LAD method.
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