B-spline estimation for partially linear varying coefficient composite quantile regression models
Jun Jin,
Chenyan Hao and
Tiefeng Ma
Communications in Statistics - Theory and Methods, 2019, vol. 48, issue 21, 5322-5335
Abstract:
In this article, a new composite quantile regression estimation (CQR) approach is proposed for partially linear varying coefficient models (PLVCM) under composite quantile loss function with B-spline approximations. The major advantage of the proposed procedures over the existing ones is easy to implement using existing software, and it requires no specification of the error distributions. Under the regularity conditions, the consistency and asymptotic normality of the estimators are also derived. Finally, a simulation study and a real data application are undertaken to assess the finite sample performance of the proposed estimation procedure.
Date: 2019
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Persistent link: https://EconPapers.repec.org/RePEc:taf:lstaxx:v:48:y:2019:i:21:p:5322-5335
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DOI: 10.1080/03610926.2018.1510006
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