{ "_id": "6a155d4cacfb0bcc41d5f96d", "Package": "BTdecayLasso", "Type": "Package", "Title": "Bradley-Terry Model with Exponential Time Decayed Log-Likelihood\nand Adaptive Lasso", "Version": "0.1.1", "Authors@R": "c(person(\"Yunpeng\", \"Zhou\", email = \"u3514104@connect.hku.hk\", role = c(\"aut\",\"cre\")),\nperson(\"Jinfeng\", \"Xu\", role = \"aut\"))", "Description": "We utilize the Bradley-Terry Model to estimate the\nabilities of teams using paired comparison data. For dynamic\napproximation of current rankings, we employ the Exponential\nDecayed Log-likelihood function, and we also apply the Lasso\npenalty for variance reduction and grouping. The main algorithm\napplies the Augmented Lagrangian Method described by Masarotto\nand Varin (2012) .", "License": "GPL (>= 2)", "LazyData": "true", "RoxygenNote": "7.2.3", "Config/pak/sysreqs": "cmake", "Repository": "https://heilokchow.r-universe.dev", "Date/Publication": "2023-12-07 08:51:51 UTC", "RemoteUrl": "https://github.com/heilokchow/btdecaylasso", "RemoteRef": "HEAD", "RemoteSha": "7c037086fab692fa6923bbf8cd6db7210131560a", "NeedsCompilation": "no", "Packaged": { "Date": "2026-05-26 08:40:25 UTC", "User": "root" }, "Author": "Yunpeng Zhou [aut, cre],\nJinfeng Xu [aut]", "Maintainer": "Yunpeng Zhou ", "MD5sum": "417fa2f923de178eb5ad988aeaf081d2", "_user": "heilokchow", "_type": "src", "_file": "BTdecayLasso_0.1.1.tar.gz", "_fileid": "b9016d07d6071d92534a88f3cf90b53bed825210494f72b90a1ea4c273e39a49", "_filesize": 213738, "_sha256": "b9016d07d6071d92534a88f3cf90b53bed825210494f72b90a1ea4c273e39a49", "_created": "2026-05-26T08:40:25.000Z", "_published": 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