{ "_id": "6a4794362f27a93436c0d827", "Package": "flashier", "Type": "Package", "Date": "2026-06-30", "Title": "Empirical Bayes Matrix Factorization", "Version": "1.0.60", "Authors@R": "c(person(\"Jason\", \"Willwerscheid\", role = c(\"aut\", \"cre\"),\nemail = \"jwillwer@providence.edu\"),\nperson(\"Peter\", \"Carbonetto\", role = \"aut\"),\nperson(\"Wei\", \"Wang\", role = \"aut\"),\nperson(\"Matthew\", \"Stephens\", role = \"aut\"),\nperson(\"Eric\", \"Weine\", role = \"ctb\"),\nperson(\"Annie\", \"Xie\", role = \"ctb\"),\nperson(\"Gao\", \"Wang\", role = \"ctb\"))", "URL": "https://github.com/willwerscheid/flashier", "BugReports": "https://github.com/willwerscheid/flashier/issues", "Description": "Implements empirical Bayes matrix factorization (EBMF), a\nflexible modeling framework for matrix factorization based on\nWang and Stephens (2021)\n. Includes many\npopular matrix factorization methods such as SVD, sparse factor\nanalysis (SFA), non-negative matrix factorization (NMF) and\nsemi-non-negative matrix factorization (semi-NMF) as special\ncases. The model fitting algorithms are implemented using a\nmodular computational framework that efficiently handles a\nvariety of data types.", "Remotes": [ "stephenslab/ebnm", "stephenslab/fastTopics" ], "License": "BSD_3_clause + file LICENSE", "Encoding": "UTF-8", "LazyData": "true", "RoxygenNote": "7.3.2", "VignetteBuilder": "knitr", "Roxygen": "list(markdown = TRUE)", "Config/pak/sysreqs": "cmake make libicu-dev libuv1-dev libssl-dev", "Repository": "https://willwerscheid.r-universe.dev", "Date/Publication": "2026-07-01 02:46:25 UTC", "RemoteUrl": "https://github.com/willwerscheid/flashier", "RemoteRef": "HEAD", "RemoteSha": "fd44811ab22d61ee905e1964175571c452fe7683", "NeedsCompilation": "no", "Packaged": { "Date": "2026-07-01 06:33:00 UTC", "User": "root" }, "Author": "Jason Willwerscheid [aut, cre],\nPeter Carbonetto [aut],\nWei Wang [aut],\nMatthew Stephens [aut],\nEric Weine [ctb],\nAnnie Xie [ctb],\nGao Wang [ctb]", "Maintainer": "Jason Willwerscheid ", "_user": "willwerscheid", 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