{ "_id": "6ae9b25e1e2c7b3a4f532ddc", "Package": "VBMS", "Title": "Variational Bayesian Algorithm for Multi-Source Heterogeneous\nModels", "Version": "1.0.0", "Authors@R": "c(person(given = \"Lu\",\nfamily = \"Luo\",\nemail = \"luolu@stu.ynu.edu.cn\",\nrole = c(\"aut\", \"cre\")),\nperson(given = \"Huiqiong\",\nfamily = \"Li\",\nrole = \"aut\"))", "Description": "A Variational Bayesian algorithm for high-dimensional\nmulti-source heterogeneous linear models. More details have\nbeen written up in a paper submitted to the journal Statistics\nin Medicine, and the details of variational Bayesian methods\ncan be found in Ray and Szabo (2021)\n. It simultaneously performs\nparameter estimation and variable selection. The algorithm\nsupports two model settings: (1) local models, where variable\nselection is only applied to homogeneous coefficients, and (2)\nglobal models, where variable selection is also performed on\nheterogeneous coefficients. Two forms of Spike-and-Slab priors\nare available: the Laplace distribution and the Gaussian\ndistribution as the Slab component.", "License": "MIT + file LICENSE", "Encoding": "UTF-8", "RoxygenNote": "7.3.2", "NeedsCompilation": "no", "Packaged": { "Date": "2026-11-03 09:46:21 UTC", "User": "root" }, "Author": "Lu Luo [aut, cre], Huiqiong Li [aut]", "Maintainer": "Lu Luo ", "Repository": "https://luluo1999.r-universe.dev", "Date/Publication": "2025-10-08 19:40:13 UTC", "RemoteUrl": "https://github.com/cran/VBMS", "RemoteRef": "HEAD", "RemoteSha": "48cbc7dee9e5dba131ae665c3ef5f67ca77a9727", "_user": "luluo1999", "_type": "src", "_file": "VBMS_1.0.0.tar.gz", "_fileid": "https://r2.ropensci.org/08dc3902ce1fb9e4e9a619ac3651f3fce6fc52c0dee089110af8be3bee67ec6e", "_filesize": 93193, "_sha256": "08dc3902ce1fb9e4e9a619ac3651f3fce6fc52c0dee089110af8be3bee67ec6e", "_expires": "2027-02-11T10:07:25.000Z", "_created": "2026-11-03T09:46:21.000Z", "_published": "2026-11-03T10:07:26.847Z", 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