Imputation-based empirical likelihood inferences for partially nonlinear quantile regression models with missing responses-Reference-Cited by-同舟云学术

Imputation-based empirical likelihood inferences for partially nonlinear quantile regression models with missing responses

Published:2022-04-06 Issue:4 Volume:106 Page:705-722
ISSN:1863-8171
Container-title:AStA Advances in Statistical Analysis
language:en
Short-container-title:AStA Adv Stat Anal

Author:

Zhou Xiaoshuang^ORCID,Zhao Peixin,Gai Yujie

Funder

Natural Science Foundation of Shandong Province

Natural Social Science Foundation of China

National Natural Science Foundation of China

Publisher

Springer Science and Business Media LLC

Subject

Applied Mathematics,Economics and Econometrics,Social Sciences (miscellaneous),Modeling and Simulation,Statistics and Probability,Analysis

Link

https://link.springer.com/content/pdf/10.1007/s10182-022-00441-z.pdf

Reference22 articles.

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2. He, X., Liang, H.: Quantile regression estimates for a class of linear and partially linear errors-in-variables models. Statistica Sinica 10, 129–140 (2000)

3. Huang, T., Chen, H.: Estimating the parametric component of nonlinear partial spline model. J Multivar Anal 99, 1665–1680 (2008)

4. Koenker, R., Bassett, G., Jr.: Regression quantiles. Econometrica 46, 33–50 (1978)

5. Lee, S.: Efficient semiparametric estimation of a partially linear quantile regression model. Econ. Theory 19, 1–31 (2003)

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