Variable Selection for Partial Linear Single-Index Model with M-Estimation

Yafeng Xia; Erzhong Chang

doi:10.2991/amsm-16.2016.40

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Variable Selection for Partial Linear Single-Index Model with M-Estimation

Yafeng Xia Erzhong Chang

Year: 2016

DOI: 10.2991/amsm-16.2016.40

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Abstract

In this paper, a method of variable selection for partial linear single-index model is proposed, which is based on the M-estimation and the adaptive LASSO. And its oracle property is established and proved. Unlike the existing M-estimator of the partial linear single-index model, the unknown link function is approximated by B-spline.

Keywords:

Estimator Spline (mechanical) Feature selection Linear model Mathematics Variable (mathematics) Oracle Index (typography) Single-index model B-spline Partial least squares regression Model selection Applied mathematics Computer science Mathematical optimization Algorithm Statistics Artificial intelligence Mathematical analysis Engineering

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Advanced Statistical Methods and Models

Physical Sciences → Mathematics → Statistics and Probability

Fault Detection and Control Systems

Physical Sciences → Engineering → Control and Systems Engineering

Statistical Methods and Inference

Physical Sciences → Mathematics → Statistics and Probability

Variable Selection for Partial Linear Single-Index Model with M-Estimation

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