{ "_id": "6a105220acfb0bcc41ca1661", "Package": "BANAM", "Type": "Package", "Date": "2024-12-03", "Title": "Bayesian Analysis of the Network Autocorrelation Model", "Version": "0.2.2", "Authors@R": "c(person(given = \"Joris\",\nfamily = \"Mulder\",\nrole = c(\"aut\", \"cre\"),\nemail = \"j.mulder3@tilburguniversity.edu\"),\nperson(given = \"Dino\",\nfamily = \"Dittrich\",\nrole = c(\"aut\", \"ctb\"),\nemail = \"dino.dittrich@gmail.com\"),\nperson(given = \"Roger\",\nfamily = \"Leenders\",\nrole = c(\"aut\", \"ctb\"),\nemail = \"r.t.a.j.leenders@tilburguniversity.edu\")\n)", "Maintainer": "Joris Mulder ", "Description": "The network autocorrelation model (NAM) can be used for\nstudying the degree of social influence regarding an outcome\nvariable based on one or more known networks. The degree of\nsocial influence is quantified via the network autocorrelation\nparameters. In case of a single network, the Bayesian methods\nof Dittrich, Leenders, and Mulder (2017)\n and Dittrich, Leenders, and\nMulder (2019) are implemented\nusing a normal, flat, or independence Jeffreys prior for the\nnetwork autocorrelation. In the case of multiple networks, the\nBayesian methods of Dittrich, Leenders, and Mulder (2020)\n are implemented using a\nmultivariate normal prior for the network autocorrelation\nparameters. Flat priors are implemented for estimating the\ncoefficients. For Bayesian testing of equality and\norder-constrained hypotheses, the default Bayes factor of Gu,\nMulder, and Hoijtink, (2018) is used\nwith the posterior mean and posterior covariance matrix of the\nNAM parameters based on flat priors as input.", "License": "GPL (>= 3)", "Encoding": "UTF-8", "LazyData": "true", "RoxygenNote": "7.2.3", "NeedsCompilation": "no", "Packaged": { "Date": "2026-05-09 09:26:04 UTC", "User": "root" }, "Author": "Joris Mulder [aut, cre], Dino Dittrich [aut, ctb], Roger\nLeenders [aut, ctb]", "Repository": "https://cran.r-universe.dev", "Date/Publication": "2024-12-03 10:30:02 UTC", "RemoteUrl": "https://github.com/cran/BANAM", "RemoteRef": "HEAD", "RemoteSha": "4f27b5530bdf5c1b58e07e9b24aa2fa7963ad07f", "MD5sum": "8e8e44e93c45261bfcd6647226fffd52", "_user": "cran", "_type": "src", "_file": "BANAM_0.2.2.tar.gz", "_fileid": "91bafcd766c57b669e92fcabe64026a23e78cd0e8ff85bd92a5afb921f6c0008", "_filesize": 645218, "_sha256": 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