{ "_id": "6ab4f0863d719c1f84097897", "Package": "bnpa", "Type": "Package", "Title": "Bayesian Networks & Path Analysis", "Version": "0.3.0", "Author": "Elias Carvalho, Joao R N Vissoci, Luciano Andrade, Wagner\nMachado, Emerson P Cabrera, Julio C Nievola", "Maintainer": "Elias Carvalho ", "Description": "This project aims to enable the method of Path Analysis to\ninfer causalities from data. For this we propose a hybrid\napproach, which uses Bayesian network structure learning\nalgorithms from data to create the input file for creation of a\nPA model. The process is performed in a semi-automatic way by\nour intermediate algorithm, allowing novice researchers to\ncreate and evaluate their own PA models from a data set. The\nreferences used for this project are: Koller, D., & Friedman,\nN. (2009). Probabilistic graphical models: principles and\ntechniques. MIT press. .\nNagarajan, R., Scutari, M., & Lèbre, S. (2013). Bayesian\nnetworks in r. Springer, 122, 125-127. Scutari, M., & Denis, J.\nB. . Scutari M (2010). Bayesian\nnetworks: with examples in R. Chapman and Hall/CRC.\n. Rosseel, Y. (2012). lavaan: An R Package\nfor Structural Equation Modeling. Journal of Statistical\nSoftware, 48(2), 1 - 36. .", "URL": "https://sites.google.com/site/bnparp/.", "License": "GPL-3", "Encoding": "UTF-8", "LazyData": "true", "RoxygenNote": "6.1.1", "NeedsCompilation": "no", "Packaged": { "Date": "2026-09-24 09:38:37 UTC", "User": "root" }, "Config/pak/sysreqs": "cmake libglpk-dev make default-jdk libicu-dev\nlibjpeg-dev libpng-dev libuv1-dev libxml2-dev zlib1g-dev", "Repository": "https://eliascarvalho.r-universe.dev", "Date/Publication": "2019-08-01 22:20:02 UTC", "RemoteUrl": "https://github.com/cran/bnpa", "RemoteRef": "HEAD", "RemoteSha": "3f27ca031b7f6fbf30264d8582970f505f8b76ea", "_user": "eliascarvalho", "_type": "src", "_file": "bnpa_0.3.0.tar.gz", "_fileid": "https://r2.ropensci.org/a1d83f447519b4c5cc902947260205bcc7c338876a813a7c52a802f4766cf465", "_filesize": 208035, "_sha256": "a1d83f447519b4c5cc902947260205bcc7c338876a813a7c52a802f4766cf465", "_expires": "2027-01-02T09:42:29.000Z", "_created": "2026-09-24T09:38:37.000Z", 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