Penalized empirical likelihood for partially linear errors-in-variables models-Reference-Cited by-同舟云学术

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Penalized empirical likelihood for partially linear errors-in-variables models

Published:2020-03-07 Issue:4 Volume:104 Page:597-623
ISSN:1863-8171
Container-title:AStA Advances in Statistical Analysis
language:en
Short-container-title:AStA Adv Stat Anal

Author:

Chen Xia^ORCID,Mao Liyue

Funder

The Youth Fund for Humanities and Social Sciences Research of Ministry of Education

Fundamental Research Funds for the Central Universities

Publisher

Springer Science and Business Media LLC

Subject

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

Link

http://link.springer.com/content/pdf/10.1007/s10182-020-00365-6.pdf

Reference48 articles.

1. Carroll, R.J., Ruppert, D., Stefanski, L.A., Crainiceanu, C.M.: Measurement Error in Nonlinear Models: A Modern Perspective, 2nd edn. Chapman and Hall-CRC, London (2006)

2. Chang, J., Tang, C.Y., Wu, T.T.: A new scope of penalized empirical likelihood with high-dimensional estimating equations. Ann. Stat. 46, 3185–3216 (2018)

3. Chen, X., Cui, H.J.: Empirical likelihood inference for parameters in a partially linear errors-in-variables model. Statistics 46, 745–757 (2012)

4. Cui, H.J., Kong, E.F.: Empirical likelihood confidence region for parameters in semi-linear errors-in-variables models. Scand. J. Stat. 33, 153–168 (2006)

5. Cui, H.J., Li, R.C.: On parameter estimation for semi-linear errors-in-variables models. J. Multivar. Anal. 64, 1–24 (1998)

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