{ "_id": "6a2530b04b233be198395d0b", "Package": "psme", "Version": "1.0.0", "Date": "2025-10-06", "Title": "Penalized Splines Mixed-Effects Models", "Authors@R": "person(\"Zheyuan\", \"Li\", role = c(\"aut\", \"cre\"),\nemail = \"zheyuan.li@bath.edu\",\ncomment = c(ORCID = \"0000-0002-7434-5947\"))", "Maintainer": "Zheyuan Li ", "Description": "Fit penalized splines mixed-effects models (a special case\nof additive models) for large longitudinal datasets. The\npackage includes a psme() function that (1) relies on package\n'mgcv' for constructing population and subject smooth functions\nas penalized splines, (2) transforms the constructed additive\nmodel to a linear mixed-effects model, (3) exploits package\n'lme4' for model estimation and (4) backtransforms the\nestimated linear mixed-effects model to the additive model for\ninterpretation and visualizaiton. See Pedersen et al. (2019)\n and Bates et al. (2015)\n for an introduction. Unlike the\ngamm() function in 'mgcv', the psme() function is fast and\nmemory-efficient, able to handle datasets with millions of\nobservations.", "License": "GPL-3", "NeedsCompilation": "no", "URL": "https://github.com/ZheyuanLi/psme", "Config/pak/sysreqs": "cmake make", "Repository": "https://zheyuanli.r-universe.dev", "Date/Publication": "2025-10-07 10:19:50 UTC", "RemoteUrl": "https://github.com/zheyuanli/psme", "RemoteRef": "HEAD", "RemoteSha": "583b42a23ce547d0b7ea6d068331b0e151d6e5e2", "Packaged": { "Date": "2026-06-07 08:45:55 UTC", "User": "root" }, "Author": "Zheyuan Li [aut, cre] (ORCID: )", "MD5sum": "1c2efb9eb1591f274af763952883574f", "_user": "zheyuanli", "_type": "src", "_file": "psme_1.0.0.tar.gz", "_fileid": "8e9fcc8c790b5b4a5172d798f6dc357a64dcc079e6c19bf6cb1c229272a7dd56", "_filesize": 115384, "_sha256": "8e9fcc8c790b5b4a5172d798f6dc357a64dcc079e6c19bf6cb1c229272a7dd56", "_created": "2026-06-07T08:45:55.000Z", "_published": "2026-06-07T08:49:52.164Z", "_distro": 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