A Comparative Study of Semiparametric Estimation in Partially Linear Single-index Models

DOI10.1080/03610918.2014.909935zbMath1346.62076OpenAlexW1963665189MaRDI QIDQ2821020

Young-Ju Kim

Publication date: 16 September 2016

Published in: Communications in Statistics - Simulation and Computation (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/03610918.2014.909935

zbMATH Keywords

boostingpenalized likelihoodpartially linear modelsingle-indexpartial splineproject pursuit regression

Mathematics Subject Classification ID

Nonparametric regression and quantile regression (62G08) Nonparametric estimation (62G05)

Cites Work

• Unnamed Item
• Smoothing noisy data with spline functions: Estimating the correct degree of smoothing by the method of generalized cross-validation
• Semiparametric least squares (SLS) and weighted SLS estimation of single-index models
• Direct estimation of the index coefficient in a single-index model
• Optimal smoothing in single-index models
• Smoothing Spline Estimation for Partially Linear Single-index Models
• Consistent Estimation of Scaled Coefficients
• Smoothing Parameter Selection in Nonparametric Regression Using an Improved Akaike Information Criterion
• Penalized Spline Estimation for Partially Linear Single-Index Models
• Smoothing Spline Gaussian Regression: More Scalable Computation via Efficient Approximation
• An Adaptive Estimation of Dimension Reduction Space
• Penalized likelihood regression: General formulation and efficient approximation
• Semiparametric Estimation of Index Coefficients

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