Covariate dimension reduction for survival data via the Gaussian process latent variable model-Reference-Cited by-同舟云学术

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Covariate dimension reduction for survival data via the Gaussian process latent variable model

Published:2015-11-03 Issue:8 Volume:35 Page:1340-1353
ISSN:0277-6715
Container-title:Statistics in Medicine
language:en
Short-container-title:Statist. Med.

Author:

Barrett James E.¹^ORCID,Coolen Anthony C. C.¹

Affiliation:

1. Institute for Mathematical and Molecular Biomedicine, King's College London; London U.K.

Funder

European Commission FP7 Imagint Project

Publisher

Wiley

Subject

Statistics and Probability,Epidemiology

Link

http://onlinelibrary.wiley.com/wol1/doi/10.1002/sim.6784/fullpdf

Reference30 articles.

1. Regression models and life tables (with discussion);Cox;Journal of the Royal Statistical Society: Series B (Methodological),1972

2. Survival analysis with high-dimensional covariates;Witten;Statistical Methods in Medical Research,2010

3. L1 penalized estimation in the Cox proportional hazards model;Goeman;Biometrical Journal,2010

4. L1-regularization path algorithm for generalized linear models;Park;Journal of the Royal Statistical Society: Series B (Statistical Methodology),2007

5. Gradient lasso for Cox proportional hazards model;Sohn;Bioinformatics,2009

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