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  "Title": "Variable Length Markov Chains ('VLMC') Models",
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  "SuggestsNote": "{astsa} mentioned in docu only.",
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  "Maintainer": "Martin Maechler <maechler@stat.math.ethz.ch>",
  "Repository": "https://mmaechler.r-universe.dev",
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      "date": "2018-10-03"
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    "char2int",
    "draw",
    "entropy",
    "entropy2",
    "id2ctxt",
    "int2alpha",
    "int2char",
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    "prt.vvec",
    "RCplot",
    "simulate.vlmc",
    "vlmc",
    "vlmc.version",
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      "title": "BNRF1 Gene DNA sequences: Epstein-Barr and Herpes",
      "object": "bnrf1",
      "file": "bnrf1.R",
      "class": [
        "factor"
      ],
      "fields": [],
      "table": false,
      "tojson": true
    },
    {
      "name": "bnrf1HV",
      "title": "BNRF1 Gene DNA sequences: Epstein-Barr and Herpes",
      "object": "bnrf1",
      "file": "bnrf1.R",
      "class": [
        "factor"
      ],
      "fields": [],
      "table": false,
      "tojson": true
    },
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      "title": "Daily Rainfall in Melbourne, Australia, 1981-1990",
      "object": "OZrain",
      "file": "OZrain.rda",
      "class": [
        "ts"
      ],
      "fields": [],
      "table": false,
      "tojson": true
    }
  ],
  "_help": [
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      "page": "alpha2int",
      "title": "`Single Character' <-> Integer Conversion for Discrete Data",
      "topics": [
        "alpha2int",
        "int2alpha"
      ]
    },
    {
      "page": "alphabet",
      "title": "The Alphabet in Use",
      "topics": [
        "alphabet",
        "alphabet.vlmc"
      ]
    },
    {
      "page": "as.dendrogram.vlmc",
      "title": "Dendrogram Construction from VLMCs",
      "topics": [
        "as.dendrogram.vlmc"
      ]
    },
    {
      "page": "bnrf1",
      "title": "BNRF1 Gene DNA sequences: Epstein-Barr and Herpes",
      "topics": [
        "bnrf1EB",
        "bnrf1HV"
      ]
    },
    {
      "page": "deviance.vlmc",
      "title": "Compute the Deviance of a Fitted VLMC Object",
      "topics": [
        "deviance.vlmc"
      ]
    },
    {
      "page": "draw.vlmc",
      "title": "Draw a \"VLMC\" Object (in ASCII) as Tree",
      "topics": [
        "draw",
        "draw.vlmc"
      ]
    },
    {
      "page": "id2ctxt",
      "title": "VLMC Context ID Conversion",
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        "id2ctxt"
      ]
    },
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      "page": "int2char",
      "title": "Character - Integer Conversion",
      "topics": [
        "char2int",
        "int2char"
      ]
    },
    {
      "page": "logLik",
      "title": "Log Likelihood of and between VLMC objects",
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        "entropy",
        "entropy2",
        "logLik.vlmc"
      ]
    },
    {
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      "title": "Daily Rainfall in Melbourne, Australia, 1981-1990",
      "topics": [
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      ]
    },
    {
      "page": "predict.vlmc",
      "title": "Prediction of VLMC for (new) Series",
      "topics": [
        "fitted.vlmc",
        "predict.vlmc",
        "print.predict.vlmc"
      ]
    },
    {
      "page": "prt.vvec",
      "title": "Recursively Print the VLMC Result Vector",
      "topics": [
        "prt.vvec"
      ]
    },
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      "page": "RCplot",
      "title": "Residuals vs Context plot",
      "topics": [
        "RCplot"
      ]
    },
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      "page": "residuals.vlmc",
      "title": "Compute Residuals of a Fitted VLMC Object",
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        "residuals.vlmc"
      ]
    },
    {
      "page": "simulate.vlmc",
      "title": "Simulate a Discrete Time Series from fitted VLMC model",
      "topics": [
        "simulate.vlmc"
      ]
    },
    {
      "page": "summary.vlmc",
      "title": "Summary of Fitted Variable Length Markov Chain (VLMC)",
      "topics": [
        "print.summary.vlmc",
        "summary.vlmc"
      ]
    },
    {
      "page": "vlmc",
      "title": "Fit a Variable Length Markov Chain (VLMC)",
      "topics": [
        "is.vlmc",
        "print.vlmc",
        "vlmc"
      ]
    },
    {
      "page": "vlmc.version",
      "title": "Version of VLMC Package",
      "topics": [
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      ]
    },
    {
      "page": "vlmctree",
      "title": "Compute the tree structure of a \"vlmc\" object",
      "topics": [
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        "str.vtree",
        "vlmctree"
      ]
    }
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