Semiparametric least squares support vector machine for accelerated failure time model

DOI10.1016/j.jkss.2010.05.002zbMath1296.62198OpenAlexW2060621138MaRDI QIDQ744593

Changha Hwang, Jooyong Shim, Choongrak Kim

Publication date: 25 September 2014

Published in: Journal of the Korean Statistical Society (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.jkss.2010.05.002

zbMATH Keywords

semiparametric modelcensored dataaccelerated failure timegeneralized cross-validationleast squares support vector machine

Mathematics Subject Classification ID

Nonparametric regression and quantile regression (62G08) Classification and discrimination; cluster analysis (statistical aspects) (62H30) Reliability and life testing (62N05)

Related Items

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

Uses Software

• bootstrap

Cites Work

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• Estimation in a linear regression model with censored data
• Estimating regression parameters using linear rank tests for censored data
• Alternative approaches to study lifetime data under different scenarios: from the PH to the modified semiparametric AFT model
• Regression analysis with randomly right-censored data
• Consistent estimation under random censorship when covariables are present
• Nonparametric Estimation from Incomplete Observations
• Linear regression with censored data
• M-estimation in censored linear models
• A Step-up Procedure for Selecting Variables Associated with Survival
• A class of semi parametric regressions for the accelerated failure time model
• Rank-based inference for the accelerated failure time model
• Survival Analysis with Median Regression Models
• Censored partial regression