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The benefit of data-based model complexity selection via prediction error curves in time-to-event data

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  • Christine Porzelius
  • Martin Schumacher
  • Harald Binder

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  • Christine Porzelius & Martin Schumacher & Harald Binder, 2011. "The benefit of data-based model complexity selection via prediction error curves in time-to-event data," Computational Statistics, Springer, vol. 26(2), pages 293-302, June.
    • Handle: RePEc:spr:compst:v:26:y:2011:i:2:p:293-302
    DOI: 10.1007/s00180-011-0236-6
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    References listed on IDEAS

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    1. 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.
    2. 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.
    3. Zhu, Mu, 2008. "Kernels and Ensembles: Perspectives on Statistical Learning," The American Statistician, American Statistical Association, vol. 62, pages 97-109, May.
    4. Gneiting, Tilmann & Raftery, Adrian E., 2007. "Strictly Proper Scoring Rules, Prediction, and Estimation," Journal of the American Statistical Association, American Statistical Association, vol. 102, pages 359-378, March.
    5. Thomas A. Gerds & Martin Schumacher, 2007. "Efron-Type Measures of Prediction Error for Survival Analysis," Biometrics, The International Biometric Society, vol. 63(4), pages 1283-1287, December.
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