_            _    _        _         _
      /\ \         /\ \ /\ \     /\_\      / /\
      \_\ \       /  \ \\ \ \   / / /     / /  \
      /\__ \     / /\ \ \\ \ \_/ / /     / / /\ \__
     / /_ \ \   / / /\ \ \\ \___/ /     / / /\ \___\
    / / /\ \ \ / / /  \ \_\\ \ \_/      \ \ \ \/___/
   / / /  \/_// / /   / / / \ \ \        \ \ \
  / / /      / / /   / / /   \ \ \   _    \ \ \
 / / /      / / /___/ / /     \ \ \ /_/\__/ / /
/_/ /      / / /____\/ /       \ \_\\ \/___/ /
\_\/       \/_________/         \/_/ \_____\/
r-survml 1.2.0
Propagated dependencies: r-survival@3.7-0 r-superlearner@2.0-29 r-mboost@2.9-11 r-iso@0.0-21 r-haldensify@0.2.3 r-gtools@3.9.5 r-fdrtool@1.2.18 r-dplyr@1.1.4 r-chernoffdist@0.1.0
Channel: guix-cran
Location: guix-cran/packages/s.scm (guix-cran packages s)
Home page: https://github.com/cwolock/survML
Licenses: GPL 3+
Synopsis: Tools for Flexible Survival Analysis Using Machine Learning
Description:

Statistical tools for analyzing time-to-event data using machine learning. Implements survival stacking for conditional survival estimation, standardized survival function estimation for current status data, and methods for algorithm-agnostic variable importance. See Wolock CJ, Gilbert PB, Simon N, and Carone M (2024) <doi:10.1080/10618600.2024.2304070>.

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