{ "_id": "6a1d471f1d7bb097a0a42490", "Package": "lsm", "Type": "Package", "Title": "Estimation of the log Likelihood of the Saturated Model", "Version": "0.2.1.5", "Date": "2025-06-02", "Authors@R": "c(\nperson(\"Jorge\", \"Villalba\", email = \"jvillalba@utb.edu.co\", role = c(\"aut\", \"cre\"), comment = c(ORCID = \"0000-0002-2888-9660\")),\nperson(\"Humberto\", \"Llinas\", email = \"hllinas@uninorte.edu.co\", role = c(\"aut\"), comment = c(ORCID = \"0000-0002-2976-5109\")),\nperson(\"Omar\", \"Fabregas\", email = \"ofabregas@uninorte.edu.co\", role = c(\"aut\"), comment = c(ORCID = \"0000-0001-6853-6280\"))\n)", "Author": "Jorge Villalba [aut, cre] (ORCID:\n), Humberto Llinas [aut]\n(ORCID: ), Omar Fabregas\n[aut] (ORCID: )", "Maintainer": "Jorge Villalba ", "Description": "When the values of the outcome variable Y are either 0 or\n1, the function lsm() calculates the estimation of the log\nlikelihood in the saturated model. This model is characterized\nby Llinas (2006, ISSN:2389-8976) in section 2.3 through the\nassumptions 1 and 2. The function LogLik() works (almost\nperfectly) when the number of independent variables K is high,\nbut for small K it calculates wrong values in some cases. For\nthis reason, when Y is dichotomous and the data are grouped in\nJ populations, it is recommended to use the function lsm()\nbecause it works very well for all K.", "Encoding": "UTF-8", "License": "MIT + file LICENSE", "RoxygenNote": "7.3.1", "LazyLoad": "yes", "LazyData": "yes", "NeedsCompilation": "no", "Packaged": { "Date": "2026-06-01 08:44:39 UTC", "User": "root" }, "Repository": "https://cran.r-universe.dev", "Date/Publication": "2025-06-02 17:30:01 UTC", "RemoteUrl": "https://github.com/cran/lsm", "RemoteRef": "HEAD", "RemoteSha": "3d296488529fcdd92e359b59e2c6af5d0ecd4628", "MD5sum": "bf841deba3320916e89a7efe6a7e2c64", "_user": "cran", "_type": "src", "_file": "lsm_0.2.1.5.tar.gz", "_fileid": "3a7dc605a83821f39797743e1159fbc5ea3ec7ca95fc2a95503ca4060f10a911", "_filesize": 219019, "_sha256": "3a7dc605a83821f39797743e1159fbc5ea3ec7ca95fc2a95503ca4060f10a911", "_created": "2026-06-01T08:44:39.000Z", "_published": "2026-06-01T08:47:27.866Z", "_distro": "noble", "_jobs": [ { 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