{ "_id": "6a32874e3efcd9bda438be30", "Package": "sahpm", "Title": "Variable Selection using Simulated Annealing", "Version": "1.0.1", "Authors@R": "c(person(\"Arnab\", \"Maity\", email = \"arnab.maity@pfizer.com\", role = c(\"aut\", \"cre\")),\nperson(\"Sanjib\", \"Basu\", email = \"sbasu@uic.edu\", role = c(\"ctb\")))", "Description": "Highest posterior model is widely accepted as a good model\namong available models. In terms of variable selection highest\nposterior model is often the true model. Our stochastic search\nprocess SAHPM based on simulated annealing maximization method\ntries to find the highest posterior model by maximizing the\nmodel space with respect to the posterior probabilities of the\nmodels. This package currently contains the SAHPM method only\nfor linear models. The codes for GLM will be added in future.", "License": "GPL-2", "Encoding": "UTF-8", "RoxygenNote": "6.1.1", "NeedsCompilation": "no", "Packaged": { "Date": "2026-06-17 11:34:40 UTC", "User": "root" }, "Author": "Arnab Maity [aut, cre], Sanjib Basu [ctb]", "Maintainer": "Arnab Maity ", "Repository": "https://maitya02.r-universe.dev", "Date/Publication": "2022-02-24 07:20:01 UTC", "RemoteUrl": "https://github.com/cran/sahpm", "RemoteRef": "HEAD", "RemoteSha": "b7b86c8412d37c968699616377716cd63347eae0", "MD5sum": "76ffb51ace53ac3571018d5cc9a9b7e8", "_user": "maitya02", "_type": "src", "_file": "sahpm_1.0.1.tar.gz", "_fileid": "046882d1643737229530565907be4224c0a0912770e9de9ea87945b3861dc3c0", "_filesize": 122207, "_sha256": "046882d1643737229530565907be4224c0a0912770e9de9ea87945b3861dc3c0", "_created": "2026-06-17T11:34:40.000Z", "_published": "2026-06-17T11:38:54.916Z", "_distro": "noble", "_jobs": [ { "job": 81884751558, "time": 221, "config": "linux-devel-x86_64", "r": "4.7.0", 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