Estimation by polynomial splines with variable selection in additive Cox models
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 consisten...
| Main Authors: | , , |
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| Other Authors: | |
| Format: | Journal Article |
| Language: | English |
| Published: |
2013
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| Subjects: | |
| Online Access: | https://hdl.handle.net/10356/99627 http://hdl.handle.net/10220/11794 |
| _version_ | 1824455172058775552 |
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| author | Zhang, Shangli Wang, Lichun Lian, Heng |
| author2 | School of Physical and Mathematical Sciences |
| author_facet | School of Physical and Mathematical Sciences Zhang, Shangli Wang, Lichun Lian, Heng |
| author_sort | Zhang, Shangli |
| collection | NTU |
| description | 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. |
| first_indexed | 2025-02-19T03:33:59Z |
| format | Journal Article |
| id | ntu-10356/99627 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2025-02-19T03:33:59Z |
| publishDate | 2013 |
| record_format | dspace |
| spelling | ntu-10356/996272020-03-07T12:34:48Z Estimation by polynomial splines with variable selection in additive Cox models Zhang, Shangli Wang, Lichun Lian, Heng School of Physical and Mathematical Sciences DRNTU::Science::Mathematics::Statistics 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. 2013-07-17T08:09:27Z 2019-12-06T20:09:38Z 2013-07-17T08:09:27Z 2019-12-06T20:09:38Z 2012 2012 Journal Article 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. https://hdl.handle.net/10356/99627 http://hdl.handle.net/10220/11794 10.1080/02331888.2012.748770 en Statistics: a journal of theoretical and applied statistics © 2012 Taylor & Francis. |
| spellingShingle | DRNTU::Science::Mathematics::Statistics Zhang, Shangli Wang, Lichun Lian, Heng Estimation by polynomial splines with variable selection in additive Cox models |
| title | Estimation by polynomial splines with variable selection in additive Cox models |
| title_full | Estimation by polynomial splines with variable selection in additive Cox models |
| title_fullStr | Estimation by polynomial splines with variable selection in additive Cox models |
| title_full_unstemmed | Estimation by polynomial splines with variable selection in additive Cox models |
| title_short | Estimation by polynomial splines with variable selection in additive Cox models |
| title_sort | estimation by polynomial splines with variable selection in additive cox models |
| topic | DRNTU::Science::Mathematics::Statistics |
| url | https://hdl.handle.net/10356/99627 http://hdl.handle.net/10220/11794 |
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