Double sparsity garrotized kernel machine in high-dimensional partially linear model-Reference-Cited by-同舟云学术

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Double sparsity garrotized kernel machine in high-dimensional partially linear model

Published:2024-03-31 Issue: Volume: Page:1-16
ISSN:0361-0918
Container-title:Communications in Statistics - Simulation and Computation
language:en
Short-container-title:Communications in Statistics - Simulation and Computation

Author:

Zhao Xinyi¹,Rong Yaohua¹,Lin Junze²,Tian Maozai³,Liang Jinwen¹

Affiliation:

1. School of Mathematics, Statistics and Mechanics, Beijing University of Technology, Beijing, China

2. Department of Economics, University of Illinois at Urbana-Champaign, Illinois, USA

3. Center for Applied Statistics, School of Statistics, Renmin University of China, Beijing, China

Funder

National Natural Science Foundation of China

National Statistical Science Research Project

Science and Technology Program of Beijing Education Commission

Publisher

Informa UK Limited

Link

https://www.tandfonline.com/doi/pdf/10.1080/03610918.2024.2329244

Reference32 articles.

1. Metabolic Syndrome and Cardiometabolic Risk Factors in the Mixed Hypercholesterolemic Populations with Respect to Gender, Age, and Obesity in Asir, Saudi Arabia

2. Automatic Feature Selection via Weighted Kernels and Regularization

3. Boyd, S., and L. Vandenberghe. 2004. Convex optimization. New York: Cambridge University Press.

4. Double sparsity kernel learning with automatic variable selection and data extraction

5. Cristianini, N., and J. Shawe-Taylor. 2000. An introduction to support vector machines and other kernel-based learning methods. New York: Cambridge University Press.

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