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Nonlinearities, (state dependent\nparameters) and random effects on all parameters are possible,\nusing either max likelihood / max a posteriori optimization\n(with optional importance sampling) or Stan's Hamiltonian Monte\nCarlo sampling. See\n\nfor details. See \nfor a detailed tutorial. Priors may be used. For the conceptual\noverview of the hierarchical Bayesian linear SDE approach, see\n.\nExogenous inputs may also be included, for an overview of such\npossibilities see\n\n. contains some tutorial blog\nposts.", "License": "GPL-3", "URL": "https://github.com/cdriveraus/ctsem", "Encoding": "UTF-8", "LazyData": "true", "ByteCompile": "true", "VignetteBuilder": "knitr, quarto", "SystemRequirements": "GNU make", "NeedsCompilation": "yes", "Biarch": "true", "Config/roxygen2/version": "8.0.0", "Config/pak/sysreqs": "cmake make libpng-dev", "Repository": "https://cdriveraus.r-universe.dev", "Date/Publication": "2026-08-18 04:39:57 UTC", "RemoteUrl": "https://github.com/cdriveraus/ctsem", "RemoteRef": "HEAD", "RemoteSha": "a0f1e69b7282c1dcaed820919ae0d8b280d076c4", "Packaged": { "Date": "2026-10-17 08:18:31 UTC", "User": "root" }, "Author": "Charles Driver [aut, cre, cph],\nManuel Voelkle [aut, cph],\nHan Oud [aut, cph],\nTrustees of Columbia University [cph]", "Maintainer": "Charles Driver ", 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