{ "_id": "6a102b81acfb0bcc41c92903", "Package": "penAFT", "Type": "Package", "Title": "Fit the Semiparameteric Accelerated Failure Time Model with\nElastic Net and Sparse Group Lasso Penalties", "Version": "0.3.2", "Authors@R": "c(person(\"Aaron J.\", \"Molstad\", email = \"amolstad@ufl.edu\", role = c(\"aut\", \"cre\"), comment = c(ORCID = \"0000-0003-0645-5105\")), person(\"Piotr M.\", \"Suder\", role = \"aut\"))", "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 .", "License": "GPL (>= 2)", "URL": "https://ajmolstad.github.io/research/", "BugReports": "https://github.com/ajmolstad/penAFT/issues", "NeedsCompilation": "yes", "Repository": "https://ajmolstad.r-universe.dev", "Date/Publication": "2024-12-03 14:51:22 UTC", "RemoteUrl": "https://github.com/ajmolstad/penaft", "RemoteRef": "HEAD", "RemoteSha": "edf51c94f6c202547e828fb517732bd1309f86d3", "Packaged": { "Date": "2026-05-13 06:34:40 UTC", "User": "root" }, "Author": "Aaron J. Molstad [aut, cre] (ORCID:\n),\nPiotr M. Suder [aut]", "Maintainer": "Aaron J. 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