articleJournal of Statistical SoftwareJan 1, 2011DIAMOND OA

Regularization Paths for Cox's Proportional Hazards Model via Coordinate Descent

Stanford University

PubMed
Indexed incrossrefdoajpubmed

Abstract

We introduce a pathwise algorithm for the Cox proportional hazards model, regularized by convex combinations of l1 and l2 penalties (elastic net). Our algorithm fits via cyclical coordinate descent, and employs warm starts to find a solution along a regularization path. We demonstrate the efficacy of our algorithm on real and simulated data sets, and find considerable speedup between our algorithm and competing methods.

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Authors

4

Topics & keywords

Keywords
  • Coordinate descent
  • Regularization (linguistics)
  • Regular polygon
  • Elastic net regularization
  • Algorithm
  • Computer science
  • Speedup
  • Proportional hazards model
UN Sustainable Development Goals
  • Climate action
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