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  "Title": "Fit the Semiparameteric Accelerated Failure Time Model with\nElastic Net and Sparse Group Lasso Penalties",
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  "Description": "The semiparametric accelerated failure time (AFT) model is\nan attractive alternative to the Cox proportional hazards\nmodel. This package provides a suite of functions for fitting\none popular rank-based estimator of the semiparametric AFT\nmodel, the regularized Gehan estimator. Specifically, we\nprovide functions for cross-validation, prediction, coefficient\nextraction, and visualizing both trace plots and\ncross-validation curves. For further details, please see Suder,\nP. M. and Molstad, A. J., (2022) Scalable algorithms for\nsemiparametric accelerated failure time models in high\ndimensions, Statistics in Medicine <doi:10.1002/sim.9264>.",
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  "URL": "https://ajmolstad.github.io/research/",
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