Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/99627
Title: Estimation by polynomial splines with variable selection in additive Cox models
Authors: Zhang, Shangli
Wang, Lichun
Lian, Heng
Keywords: DRNTU::Science::Mathematics::Statistics
Issue Date: 2012
Source: Zhang, S., Wang, L., & Lian, H. (2012). Estimation by polynomial splines with variable selection in additive Cox models. Statistics: A Journal of Theoretical and Applied Statistics, 1-14.
Series/Report no.: Statistics: a journal of theoretical and applied statistics
Abstract: In this article, we consider penalized variable selection in additive Cox models based on (group) smoothly clipped absolute deviation penalty and hence widen the scope of applicability of penalized variable selection to semiparametric models for censored data.We demonstrate the asymptotic consistency in model selection and convergence rate in estimation. Our simulation study emphasizes comparison of several different criteria for tuning parameter selection and also compares two appropriate definitions of the degrees of freedom in additive models.
URI: https://hdl.handle.net/10356/99627
http://hdl.handle.net/10220/11794
DOI: http://dx.doi.org/10.1080/02331888.2012.748770
Rights: © 2012 Taylor & Francis.
Fulltext Permission: none
Fulltext Availability: No Fulltext
Appears in Collections:SPMS Journal Articles

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