{ "_id": "6a495d3977d6db3f2f964d46", "Package": "hal9001", "Title": "The Scalable Highly Adaptive Lasso", "Version": "0.4.6", "Authors@R": "c(\nperson(\"Jeremy\", \"Coyle\", email = \"jeremyrcoyle@gmail.com\",\nrole = c(\"aut\", \"cre\"),\ncomment = c(ORCID = \"0000-0002-9874-6649\")),\nperson(\"Nima\", \"Hejazi\", email = \"nh@nimahejazi.org\",\nrole = \"aut\",\ncomment = c(ORCID = \"0000-0002-7127-2789\")),\nperson(\"Rachael\", \"Phillips\", email = \"rachaelvphillips@berkeley.edu\",\nrole = \"aut\", comment = c(ORCID = \"0000-0002-8474-591X\")),\nperson(\"Lars\", \"van der Laan\", email = \"vanderlaanlars@yahoo.com\",\nrole = \"aut\"),\nperson(\"David\", \"Benkeser\", email = \"benkeser@emory.edu\",\nrole = \"ctb\",\ncomment = c(ORCID = \"0000-0002-1019-8343\")),\nperson(\"Oleg\", \"Sofrygin\", email = \"oleg.sofrygin@gmail.com\",\nrole = \"ctb\"),\nperson(\"Weixin\", \"Cai\", email = \"wcai@berkeley.edu\",\nrole = \"ctb\",\ncomment = c(ORCID = \"0000-0003-2680-3066\")),\nperson(\"Mark\", \"van der Laan\", email = \"laan@berkeley.edu\",\nrole = c(\"aut\", \"cph\", \"ths\"),\ncomment = c(ORCID = \"0000-0003-1432-5511\"))\n)", "Description": "A scalable implementation of the highly adaptive lasso\nalgorithm, including routines for constructing sparse matrices\nof basis functions of the observed data, as well as a custom\nimplementation of Lasso regression tailored to enhance\nefficiency when the matrix of predictors is composed\nexclusively of indicator functions. For ease of use and\nincreased flexibility, the Lasso fitting routines invoke code\nfrom the 'glmnet' package by default. The highly adaptive lasso\nwas first formulated and described by MJ van der Laan (2017)\n, with practical demonstrations of\nits performance given by Benkeser and van der Laan (2016)\n. 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