M-estimators for single-index model using B-spline |
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Authors: | Qingming Zou Zhongyi Zhu |
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Affiliation: | 1. School of Economics and Management, University of South China, Hunan, 421001, People’s Republic of China 2. Department of Statistics, Fudan University, Shanghai, 200433, People’s Republic of China
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Abstract: | The single-index model is an important tool in multivariate nonparametric regression. This paper deals with M-estimators for the single-index model. Unlike the existing M-estimator for the single-index model, the unknown link function is approximated by B-spline and M-estimators for the parameter and the nonparametric component are obtained in one step. The proposed M-estimator of unknown function is shown to attain the convergence rate as that of the optimal global rate of convergence of estimators for nonparametric regression according to Stone (Ann Stat 8:1348–1360, 1980; Ann Stat 10:1040–1053, 1982), and the M-estimator of parameter is $sqrt{n}$ -consistent and asymptotically normal. A small sample simulation study showed that the M-estimators proposed in this paper are robust. An application to real data illustrates the estimator’s usefulness. |
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