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Communications in Statistics - Theory and Methods Volume 48, 2019 - Issue 21
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Original Articles

B-spline estimation for partially linear varying coefficient composite quantile regression models

Jun JinStatistics College, Southwestern University of Finance and Economics, Sichuan, China;
,
Chenyan HaoSchool of Mathematics and Statistics, Guizhou University, Guizhou, China
&
Tiefeng MaStatistics College, Southwestern University of Finance and Economics, Sichuan, China; Correspondence[email protected]
Pages 5322-5335 | Received 15 Apr 2018, Accepted 06 Aug 2018, Published online: 23 Oct 2018

Citations (4)

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Bao-Hua Wang & Han-Ying Liang. (2022) Empirical likelihood in varying-coefficient quantile regression with missing observations. Communications in Statistics - Theory and Methods 51:1, pages 267-283.
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Articles from other publishers (3)

Bao Hua Wang & Han Ying Liang. (2023) Quantile Regression of Ultra-high Dimensional Partially Linear Varying-coefficient Model with Missing Observations. Acta Mathematica Sinica, English Series 39:9, pages 1701-1726.
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文杰 毛. (2022) Analysis of AIDS Data Based on Composite Quantile Regression. Advances in Applied Mathematics 11:10, pages 7248-7256.
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Jun Jin, Tiefeng Ma, Jiajia Dai & Shuangzhe Liu. (2020) Penalized weighted composite quantile regression for partially linear varying coefficient models with missing covariates. Computational Statistics 36:1, pages 541-575.
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