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  "Package": "hhsmm",
  "Date": "2022-2-7",
  "Title": "Hidden Hybrid Markov/Semi-Markov Model Fitting",
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  "Authors@R": "c(person(\"Morteza\", \"Amini\", role = c(\"aut\", \"cre\",\"cph\"),\nemail = \"morteza.amini@ut.ac.ir\"),\nperson(\"Afarin\", \"Bayat\", role = \"aut\"),\nperson(\"Reza\", \"Salehian\", role = \"aut\"))",
  "Description": "Develops algorithms for fitting, prediction, simulation\nand initialization of the hidden hybrid Markov/semi-Markov\nmodel, introduced by Guedon (2005)\n<doi:10.1016/j.csda.2004.05.033>, which also includes several\ntools for handling missing data, nonparametric mixture of\nB-splines emissions (Langrock et al., 2015\n<doi:10.1111/biom.12282>), fitting regime switching regression\n(Kim et al., 2008 <doi:10.1016/j.jeconom.2007.10.002>) and\nauto-regressive hidden hybrid Markov/semi-Markov model, and\nmany other useful tools (read for more description:\n<arXiv:2109.12489>).",
  "License": "GPL-3",
  "RdMacros": "Rdpack",
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  "BugReports": "https://github.com/mortamini/hhsmm/issues",
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  "Repository": "https://mortamini.r-universe.dev",
  "Date/Publication": "2022-08-27 03:41:29 UTC",
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  "Author": "Morteza Amini [aut, cre, cph],\nAfarin Bayat [aut],\nReza Salehian [aut]",
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    "mixmvnorm_mstep",
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    "rmixar",
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    "train_test_split"
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      "page": "additive_reg_mstep",
      "title": "the M step function of the EM algorithm",
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      "topics": [
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      "title": "weighted covariance for data with missing values",
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    {
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      "title": "pdf of the mixture of Gaussian linear (Markov-switching) models for hhsmm",
      "topics": [
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    },
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      "title": "pdf of the mixture of multivariate normals for hhsmm",
      "topics": [
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    },
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      "page": "dnonpar",
      "title": "pdf of the mixture of B-splines for hhsmm",
      "topics": [
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    },
    {
      "page": "dnorm_additive_reg",
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      ]
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      "title": "convert to hhsmm data",
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      "title": "hhsmm model fit",
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    {
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