Semivarying coefficient least-squares support vector regression for analyzing high-dimensional gene-environmental data

DOI10.1080/02664763.2017.1371676OpenAlexW2751510324MaRDI QIDQ5036421

Changha Hwang, Jooyong Shim, Insuk Sohn, Sunjoo Jeong

Publication date: 23 February 2022

Published in: Journal of Applied Statistics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/02664763.2017.1371676

zbMATH Keywords

semiparametric regressionsurvival datageneralized cross validationvariable selectiongene-environment interactionmain effectvarying coefficient regressionleast-squares support vector regressionsemivarying coefficient

Mathematics Subject Classification ID

Applications of statistics (62Pxx)

Related Items (1)

Robust gene–environment interaction analysis using penalized trimmed regression

Cites Work

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• Estimation and inference of semi-varying coefficient models with heteroscedastic errors
• Semiparametric least squares support vector machine for accelerated failure time model
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• Regression analysis with randomly right-censored data
• Smoothing noisy data with spline functions: Estimating the correct degree of smoothing by the method of generalized cross-validation
• Adaptive semi-varying coefficient model selection
• Nonparametric Estimation from Incomplete Observations

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