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  "Title": "Fitting Markov-Modulated Linear Regression Models",
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  "Authors@R": "c(\nperson(\"Nadezda\", \"Spiridovska\", email = \"Spiridovska.N@tsi.lv\", role = c(\"aut\", \"cre\")),\nperson(\"Diana\", \"Santalova\", role = \"ctb\"))",
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  "Description": "A set of tools for fitting Markov-modulated linear\nregression, where responses Y(t) are time-additive, and model\noperates in the external environment, which is described as a\ncontinuous time Markov chain with finite state space. Model is\nproposed by Alexander Andronov (2012) <arXiv:1901.09600v1> and\nalgorithm of parameters estimation is based on eigenvalues and\neigenvectors decomposition. Markov-switching regression models\nhave the same idea of varying the regression parameters\nrandomly in accordance with external environment. The\ndifference is that for Markov-modulated linear regression model\nthe external environment is described as a continuous-time\nhomogeneous irreducible Markov chain with known parameters\nwhile switching models consider Markov chain as unobserved and\nestimation procedure involves estimation of transition matrix.\nThese models have significant differences in terms of the\nanalytical approach. Also, package provides a set of data\nsimulation tools for Markov-modulated linear regression (for\nacademical/research purposes). Research project No.\n1.1.1.2/VIAA/1/16/075.",
  "License": "GPL (>= 2)",
  "Encoding": "UTF-8",
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  "NeedsCompilation": "no",
  "Packaged": {
    "Date": "2026-05-25 06:24:59 UTC",
    "User": "root"
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  "Author": "Nadezda Spiridovska [aut, cre], Diana Santalova [ctb]",
  "Repository": "https://nadezdaspiridovska.r-universe.dev",
  "Date/Publication": "2020-01-09 11:30:11 UTC",
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    "B_est",
    "randomizeInitState",
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    "VarY",
    "Xreg",
    "Ysimulation"
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      "title": "Calculating the average sojourn time in each state",
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      ]
    },
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      "title": "Estimantion of unknown Markov-modulated linear regression model parameters using GLSM",
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        "B_est"
      ]
    },
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        "randomizeInitState"
      ]
    },
    {
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      ]
    },
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      "title": "Transformation of regressors' matrix X. Data preparation stage for simulation",
      "topics": [
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      ]
    },
    {
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      "title": "Estimantion of the variance of the response Y",
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    },
    {
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      "title": "Preparing data for parameter estimation procedure",
      "topics": [
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      ]
    },
    {
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      ]
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