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Rank-based estimation in varying coefficient partially functional linear regression models.
- Source :
- Communications in Statistics: Theory & Methods; 2022, Vol. 51 Issue 1, p212-225, 14p
- Publication Year :
- 2022
-
Abstract
- This paper focuses on robust estimation for varying coefficient partially functional linear regression model (VCPFLM) without specification of the error distributions. The proposed estimators of the nonparametric coefficients and slope function are based on B-spline approximation and rank regression, which demonstrates that the proposed estimation is robust for non-normal error distributions compared with that of least square estimate. In addition, the optimal convergence rates of the estimators are established under some mild regularity conditions. Finally, simulation study and a real data analysis are conducted to illustrate the finite sample performance of the proposed method. [ABSTRACT FROM AUTHOR]
- Subjects :
- REGRESSION analysis
NONPARAMETRIC estimation
LEAST squares
DATA analysis
Subjects
Details
- Language :
- English
- ISSN :
- 03610926
- Volume :
- 51
- Issue :
- 1
- Database :
- Complementary Index
- Journal :
- Communications in Statistics: Theory & Methods
- Publication Type :
- Academic Journal
- Accession number :
- 154583070
- Full Text :
- https://doi.org/10.1080/03610926.2020.1747079