{ "_id": "6a1effa0b401979e7341aa98", "Package": "HMMHSMM", "Type": "Package", "Title": "Inference and Estimation of Hidden Markov Models and Hidden\nSemi-Markov Models", "Version": "0.1.0", "Authors@R": "c(person(\"Aimee\", \"Cody\", email = \"codai942@student.otago.ac.nz\", role = c(\"aut\")), person(\"Ting\", \"Wang\",email = \"ting.wang@otago.ac.nz\", role = c(\"cre\", \"ctb\"), comment = \"Research Supervisor\"))", "Maintainer": "Ting Wang ", "Description": "Provides flexible maximum likelihood estimation and\ninference for Hidden Markov Models (HMMs) and Hidden\nSemi-Markov Models (HSMMs), as well as the underlying systems\nin which they operate. The package supports a wide range of\nobservation and dwell-time distributions, offering a flexible\nmodelling framework suitable for diverse practical data.\nEfficient implementations of the forward-backward and Viterbi\nalgorithms are provided via 'Rcpp' for enhanced computational\nperformance. Additional functionality includes model\nsimulation, residual analysis, non-initialised estimation,\nlocal and global decoding, calculation of diverse information\ncriteria, computation of confidence intervals using parametric\nbootstrap methods, numerical covariance matrix estimation, and\ncomprehensive visualisation functions for interpreting the\ndata-generating processes inferred from the models. Methods\nfollow standard approaches described by Guédon (2003)\n, Zucchini and MacDonald (2009,\nISBN:9781584885733), and O'Connell and Højsgaard (2011)\n.", "License": "GPL-3", "Encoding": "UTF-8", "LazyData": "true", "RoxygenNote": "7.3.2", "NeedsCompilation": "yes", "Packaged": { "Date": "2026-05-18 09:12:56 UTC", "User": "root" }, "Author": "Aimee Cody [aut], Ting Wang [cre, ctb] (Research Supervisor)", "Repository": "https://cran.r-universe.dev", "Date/Publication": "2025-12-18 14:20:10 UTC", "RemoteUrl": "https://github.com/cran/HMMHSMM", "RemoteRef": "HEAD", "RemoteSha": "89b811c1c0f7cd9cce4d16b20e1fdd4bf49fb607", "MD5sum": "67a7d9b1bad9805ae256ed93559c6dc3", "_user": "cran", "_type": "src", "_file": "HMMHSMM_0.1.0.tar.gz", "_fileid": "93edb0d2a1029b7f0e2ce5266824e3511604edc103ec0428347ade9e0bb61390", "_filesize": 420261, "_sha256": "93edb0d2a1029b7f0e2ce5266824e3511604edc103ec0428347ade9e0bb61390", "_created": "2026-05-18T09:12:56.000Z", "_published": 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