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Variable Selection for Partially Linear Varying Coefficient Transformation Models with Censored Data

Author(s): Jiang Du | Zhongzhan Zhang | Ying Lu

Journal: Open Journal of Statistics
ISSN 2161-718X

Volume: 02;
Issue: 05;
Start page: 565;
Date: 2012;
Original page

Keywords: Variable Selection | Maximum Likelihood Estimation | Spline Smoothing

In this paper, we study the problem of variable selection for varying coefficient transformation models with censored data. We fit the varying coefficient transformation models by maximizing the marginal likelihood subject to a shrink- age-type penalty, which encourages sparse solutions and hence facilitates the process of variable selection. We further provide an efficient computation algorithm to implement the proposed methods. A simulation study is conducted to evaluate the performance of the proposed methods and a real dataset is analyzed as an illustration.
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