{ "_id": "6a44f7fc6ff6f23575520040", "Package": "HVS", "Title": "Hypergraph Variable Selection", "Version": "1.0.0", "Authors@R": "c( person(given = \"Toby\",\nfamily = \"Kenney\",\nrole = \"cre\",\nemail = \"tkenney@mathstat.dal.ca\"),\nperson(given = \"Sarah\",\nfamily = \"Organ\",\nrole = \"aut\"))", "Description": "Performs hypergraph-based setwise variable selection with\nfalse discovery rate control (Organ, Kenney & Gu, 2026,\n). The idea is, in addition to\nselecting individual predictors when there is sufficient\nevidence, to also test all pairs of predictors, and when there\nis insufficient evidence to be sure which is the true\npredictor, it will select possibly overlapping pairs, for which\nthere is strong evidence that at least one is a true predictor.\nThe method is designed to control a generalised false discovery\nrate, where discoveries are counted based on the number of\nindependent sets. The function of this package is similar to\nthe 'hypergraph.sizing' package, but this package is optimised\nfor faster computation in the case where we test all pairs of\npredictors. The package also includes functions for counting\nindependent sets in a graph or hypergraph, either exactly or\napproximately. There is also a very limited function for\nisotonic regression, which is designed for fast computation in\nthe specific case needed for hypergraph variable selection,\nrather than for general use.", "License": "GPL-3", "Encoding": "UTF-8", "NeedsCompilation": "yes", "Maintainer": "Toby Kenney ", "Packaged": { "Date": "2026-07-01 11:16:45 UTC", "User": "root" }, "Author": "Toby Kenney [cre], Sarah Organ [aut]", "Repository": "https://tjk23.r-universe.dev", "Date/Publication": "2026-06-30 11:30:20 UTC", "RemoteUrl": "https://github.com/cran/HVS", "RemoteRef": "HEAD", "RemoteSha": "92c430785a94d45d7e4082bd24017b51a7c8f147", "MD5sum": "50c1a71b21b1e724a65eeab9d12991ed", "_user": "tjk23", "_type": "src", "_file": "HVS_1.0.0.tar.gz", "_fileid": "64f50e347f4fb3b0195dfe4060686f7c0659d219121972742809062d5531ddef", "_filesize": 119027, "_sha256": "64f50e347f4fb3b0195dfe4060686f7c0659d219121972742809062d5531ddef", "_created": "2026-07-01T11:16:45.000Z", "_published": "2026-07-01T11:20:28.568Z", 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