Unbiased split variable selection for random survival forests using maximally selected rank statistics-Reference-Cited by-同舟云学术

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Unbiased split variable selection for random survival forests using maximally selected rank statistics

Published:2017-01-15 Issue:8 Volume:36 Page:1272-1284
ISSN:0277-6715
Container-title:Statistics in Medicine
language:en
Short-container-title:Statist. Med.

Author:

Wright Marvin N.¹,Dankowski Theresa¹,Ziegler Andreas¹²³⁴

Affiliation:

1. Institut für Medizinische Biometrie und Statistik; Universität zu Lübeck, Universitätsklinikum Schleswig-Holstein; Campus Lübeck Lübeck Germany

2. Zentrum für Klinische Studien; Universität zu Lübeck; Lübeck Germany

3. School of Mathematics, Statistics and Computer Science; University of KwaZulu-Natal; Pietermaritzburg South Africa

4. Deutsches Zentrum für Herz-Kreislauf-Forschung; Standort Hamburg/Kiel/Lübeck; Lübeck Germany

Publisher

Wiley

Subject

Statistics and Probability,Epidemiology

Reference55 articles.

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

2. The lasso method for variable selection in the Cox model;Tibshirani;Statistics in Medicine,1997

3. Random forests;Breiman;Machine Learning,2001

4. Exponential survival trees;Davis;Statistics in Medicine,1989

5. Bagging survival trees;Hothorn;Statistics in Medicine,2004

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