Back-fitting Estimation of Semiparametric Partially Linear Varying-coefficient Models with PCA

DOI

10.2991/emcs-15.2015.19How to use a DOI?

Keywords

Partially linear varying-coefficient model; Principal component analysis; Back-fitting procedure; Multi-collinearity; Semi-parametric estimation

Abstract

This paper investigates the estimation problem of semi-parametric partially linear varying-coefficient models by the technique of back-fitting. In order to avoid the disturbance of multi-collinearity and improve estimation efficiency, we apply principal component analysis to semi-parametric partially linear varying-coefficient models due to principal components are those uncorrelated linear combinations. And then we obtain the estimators of original parametric component and nonparametric component respectively. Model estimation and some statistic inferences about the property of the estimators are also derived theoretically.

Copyright

© 2015, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Mingxing Zhang
AU  - ZiXin Liu
AU  - Jiannan Qiao
PY  - 2015/01
DA  - 2015/01
TI  - Back-fitting Estimation of Semiparametric Partially Linear Varying-coefficient Models with PCA
BT  - Proceedings of the International Conference on Education, Management, Commerce and Society
PB  - Atlantis Press
SP  - 84
EP  - 89
SN  - 2352-5398
UR  - https://doi.org/10.2991/emcs-15.2015.19
DO  - 10.2991/emcs-15.2015.19
ID  - Zhang2015/01
ER  -