{
  "_id": "6a1ee28db401979e73410c11",
  "Package": "synthesis",
  "Title": "Generate Synthetic Data from Statistical Models",
  "Version": "1.2.5",
  "Authors@R": "person(given = \"Ze\",\nfamily = \"Jiang\",\nrole = c(\"aut\", \"cre\"),\nemail = \"ze.jiang@unsw.edu.au\",\ncomment = c(ORCID = \"0000-0002-3472-0829\"))",
  "Author": "Ze Jiang [aut, cre] (<https://orcid.org/0000-0002-3472-0829>)",
  "Maintainer": "Ze Jiang <ze.jiang@unsw.edu.au>",
  "Description": "Generate synthetic time series from commonly used\nstatistical models, including linear, nonlinear and chaotic\nsystems. Applications to testing methods can be found in Jiang,\nZ., Sharma, A., & Johnson, F. (2019)\n<doi:10.1016/j.advwatres.2019.103430> and Jiang, Z., Sharma,\nA., & Johnson, F. (2020) <doi:10.1029/2019WR026962> associated\nwith an open-source tool by Jiang, Z., Rashid, M. M., Johnson,\nF., & Sharma, A. (2020) <doi:10.1016/j.envsoft.2020.104907>.",
  "License": "GPL (>= 3)",
  "Encoding": "UTF-8",
  "URL": "https://github.com/zejiang-unsw/synthesis#readme",
  "BugReports": "https://github.com/zejiang-unsw/synthesis/issues",
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  "Repository": "https://zejiang-unsw.r-universe.dev",
  "Date/Publication": "2024-06-24 21:09:11 UTC",
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      "date": "2020-11-05"
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    "data.gen.BUWO",
    "data.gen.circles",
    "data.gen.Duffing",
    "data.gen.fbm",
    "data.gen.fm1",
    "data.gen.fm2",
    "data.gen.gbm",
    "data.gen.Henon",
    "data.gen.HL",
    "data.gen.LGSS",
    "data.gen.Logistic",
    "data.gen.Lorenz",
    "data.gen.nl1",
    "data.gen.nl2",
    "data.gen.Rossler",
    "data.gen.rw",
    "data.gen.spirals",
    "data.gen.SW",
    "data.gen.tar",
    "data.gen.tar1",
    "data.gen.tar2"
  ],
  "_help": [
    {
      "page": "data.gen.affine",
      "title": "Generate an affine error model.",
      "topics": [
        "data.gen.affine"
      ]
    },
    {
      "page": "data.gen.ar1",
      "title": "Generate predictor and response data from AR1 model.",
      "topics": [
        "data.gen.ar1"
      ]
    },
    {
      "page": "data.gen.ar4",
      "title": "Generate predictor and response data from AR4 model.",
      "topics": [
        "data.gen.ar4"
      ]
    },
    {
      "page": "data.gen.ar9",
      "title": "Generate predictor and response data from AR9 model.",
      "topics": [
        "data.gen.ar9"
      ]
    },
    {
      "page": "data.gen.blobs",
      "title": "Gaussian Blobs",
      "topics": [
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    },
    {
      "page": "data.gen.bm",
      "title": "Generate a time series of Brownian motion.",
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    },
    {
      "page": "data.gen.BUWO",
      "title": "Generate build-up and wash-off model for water quality modeling",
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    },
    {
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      "title": "Circles",
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      "title": "Duffing map",
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      ]
    },
    {
      "page": "data.gen.fbm",
      "title": "Generate a time series of fractional Brownian motion.",
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      "title": "Friedman with independent uniform variates",
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      "page": "data.gen.gbm",
      "title": "Generate a time series of geometric Brownian motion.",
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    },
    {
      "page": "data.gen.Henon",
      "title": "Henon map",
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    {
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      "title": "Generate predictor and response data: Hysteresis Loop",
      "topics": [
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    },
    {
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      "title": "Linear Gaussian state-space model",
      "topics": [
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    },
    {
      "page": "data.gen.Logistic",
      "title": "Logistic map",
      "topics": [
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    },
    {
      "page": "data.gen.Lorenz",
      "title": "Lorenz system",
      "topics": [
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      "title": "Nonlinear system with independent/correlate covariates",
      "topics": [
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      "title": "Nonlinear system with Exogenous covariates",
      "topics": [
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    },
    {
      "page": "data.gen.norm",
      "title": "Generate correlated normal variates",
      "topics": [
        "data.gen.norm"
      ]
    },
    {
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      "title": "Rössler system",
      "topics": [
        "data.gen.Rossler"
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    },
    {
      "page": "data.gen.rw",
      "title": "Generate Random walk time series.",
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        "data.gen.rw"
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    },
    {
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      "title": "Spirals",
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        "data.gen.SW"
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    },
    {
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      ]
    },
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      "title": "Generate predictor and response data from TAR1 model.",
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        "data.gen.tar1"
      ]
    },
    {
      "page": "data.gen.tar2",
      "title": "Generate predictor and response data from TAR2 model.",
      "topics": [
        "data.gen.tar2"
      ]
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    {
      "page": "data.gen.unif",
      "title": "Generate correlated uniform variates",
      "topics": [
        "data.gen.unif"
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    }
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  "_rundeps": [
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      "title": "synthesis",
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      "headings": [
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        "Overview",
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