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Variable selection in L1 penalized censored regression  

Hwang, Chang-Ha (Department of Statistics, Dankook University)
Kim, Mal-Suk (Division of Computer Technology, Yeungnam College of Science & Technology)
Shi, Joo-Yong (Department of Data Science, Inje University)
Publication Information
Journal of the Korean Data and Information Science Society / v.22, no.5, 2011 , pp. 951-959 More about this Journal
Abstract
The proposed method is based on a penalized censored regression model with L1-penalty. We use the iteratively reweighted least squares procedure to solve L1 penalized log likelihood function of censored regression model. It provide the efficient computation of regression parameters including variable selection and leads to the generalized cross validation function for the model selection. Numerical results are then presented to indicate the performance of the proposed method.
Keywords
Censored regression model; generalized cross validation function; iteratively reweighted least squares procedure; L1-penalty; variable selection;
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Times Cited By KSCI : 4  (Citation Analysis)
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