Allowing for mandatory covariates in boosting estimation of sparse high-dimensional survival models-Reference-Cited by-同舟云学术

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Allowing for mandatory covariates in boosting estimation of sparse high-dimensional survival models

Published:2008-01-10 Issue:1 Volume:9 Page:
ISSN:1471-2105
Container-title:BMC Bioinformatics
language:en
Short-container-title:BMC Bioinformatics

Author:

Binder Harald,Schumacher Martin

Publisher

Springer Science and Business Media LLC

Subject

Applied Mathematics,Computer Science Applications,Molecular Biology,Biochemistry,Structural Biology

Link

http://link.springer.com/content/pdf/10.1186/1471-2105-9-14.pdf

Reference25 articles.

1. Bühlmann P, Hothorn T: Boosting Algorithms: Regularization, Prediction and Model Fitting. Statistical Science 2008. to appear

2. Park MY, Hastie T: L1-Regularization Path Algorithms for Generalized Linear Models. Journal of the Royal Statistical Society B 2007, 69(4):659–677. 10.1111/j.1467-9868.2007.00607.x

3. Tutz G, Binder H: Boosting Ridge Regression. Computational Statistics & Data Analysis 2007, 51(12):6044–6059. 10.1016/j.csda.2006.11.041

4. Tibshirani R: The Lasso Method for Variable Selection in the Cox Model. Statistics in Medicine 1997, 16(4):385–395. 10.1002/(SICI)1097-0258(19970228)16:4<385::AID-SIM380>3.0.CO;2-3

5. Ma S, Huang J: Additive Risk Survival Model with Microarray Data. BMC Bioinformatics 2007., 8(192):

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