The benefit of data-based model complexity selection via prediction error curves in time-to-event data
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Volume (Year): 26 (2011)
Issue (Month): 2 (June)
Pages: 293-302
| Handle: | RePEc:spr:compst:v:26:y:2011:i:2:p:293-302 |
| Contact details of provider: | Web page: http://www.springerlink.com/link.asp?id=120306
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References listed on IDEAS
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- Zhu, Mu, 2008. "Kernels and Ensembles: Perspectives on Statistical Learning," The American Statistician, American Statistical Association, vol. 62, pages 97-109, May.
- Ishwaran, Hemant & Kogalur, Udaya B. & Gorodeski, Eiran Z. & Minn, Andy J. & Lauer, Michael S., 2010. "High-Dimensional Variable Selection for Survival Data," Journal of the American Statistical Association, American Statistical Association, vol. 105(489), pages 205-217.
- Binder Harald & Schumacher Martin, 2008. "Adapting Prediction Error Estimates for Biased Complexity Selection in High-Dimensional Bootstrap Samples," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 7(1), pages 1-28, March.
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