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  "Title": "Sparse Estimation of Large Time Series Models",
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  "Authors@R": "c(\nperson(\"Ines\", \"Wilms\", email = \"i.wilms@maastrichtuniversity.nl\", role = c(\"cre\",\"aut\")),\nperson(\"David S.\", \"Matteson\", email = \"matteson@cornell.edu\", role = \"aut\"),\nperson(\"Jacob\", \"Bien\", email = \"jbien@usc.edu\", role = \"aut\"),\nperson(\"Sumanta\", \"Basu\", email = \"sumbose@cornell.edu\", role = \"aut\"),\nperson(\"Will\", \"Nicholson\", email = \"wbn8@cornell.edu\", role = \"aut\"),\nperson(\"Enrico\", \"Wegner\", email = \"e.wegner@student.maastrichtuniversity.nl\", role = \"aut\"))",
  "Maintainer": "Ines Wilms <i.wilms@maastrichtuniversity.nl>",
  "Description": "Estimation of large Vector AutoRegressive (VAR), Vector\nAutoRegressive with Exogenous Variables X (VARX) and Vector\nAutoRegressive Moving Average (VARMA) Models with Structured\nLasso Penalties, see Nicholson, Wilms, Bien and Matteson (2020)\n<https://jmlr.org/papers/v21/19-777.html> and Wilms, Basu, Bien\nand Matteson (2021) <doi:10.1080/01621459.2021.1942013>.",
  "License": "GPL (>= 2)",
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  "URL": "https://github.com/ineswilms/bigtime",
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  "Repository": "https://ineswilms.r-universe.dev",
  "Date/Publication": "2023-08-21 16:30:07 UTC",
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    "plot_cv",
    "recursiveforecast",
    "simVAR",
    "sparseVAR",
    "sparseVARMA",
    "sparseVARX"
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      "title": "VARX Time Series Example ('varx.example')",
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      "class": [
        "matrix",
        "array"
      ],
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        "X1",
        "X2",
        "X3"
      ],
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      "table": true,
      "tojson": true
    },
    {
      "name": "Y.var",
      "title": "VAR Time Series Example ('var.example')",
      "object": "var.example",
      "class": [
        "matrix",
        "array"
      ],
      "fields": [
        "Y1",
        "Y2",
        "Y3",
        "Y4",
        "Y5"
      ],
      "rows": 200,
      "table": true,
      "tojson": true
    },
    {
      "name": "Y.varma",
      "title": "VARMA Time Series Example ('varma.example')",
      "object": "varma.example",
      "class": [
        "matrix",
        "array"
      ],
      "fields": [
        "Y1",
        "Y2",
        "Y3"
      ],
      "rows": 200,
      "table": true,
      "tojson": true
    },
    {
      "name": "Y.varx",
      "title": "VARX Time Series Example ('varx.example')",
      "object": "varx.example",
      "class": [
        "matrix",
        "array"
      ],
      "fields": [
        "Y1",
        "Y2",
        "Y3"
      ],
      "rows": 200,
      "table": true,
      "tojson": true
    }
  ],
  "_help": [
    {
      "page": "bigtime",
      "title": "bigtime: A package for obtaining sparse estimates of large time series models.",
      "topics": [
        "bigtime-package",
        "bigtime"
      ]
    },
    {
      "page": "create_rand_coef_mat",
      "title": "Creates a random coefficient matrix",
      "topics": [
        "create_rand_coef_mat"
      ]
    },
    {
      "page": "diagnostics_plot",
      "title": "Creates a Diagnostic Plot",
      "topics": [
        "diagnostics_plot"
      ]
    },
    {
      "page": "diagnostics_plot.bigtime.VAR",
      "title": "diagnostics_plot function for VAR models",
      "topics": [
        "diagnostics_plot.bigtime.VAR"
      ]
    },
    {
      "page": "diagnostics_plot.bigtime.VARMA",
      "title": "diagnostics_plot function for VARMA models",
      "topics": [
        "diagnostics_plot.bigtime.VARMA"
      ]
    },
    {
      "page": "diagnostics_plot.bigtime.VARX",
      "title": "diagnostics_plot function for VARX models",
      "topics": [
        "diagnostics_plot.bigtime.VARX"
      ]
    },
    {
      "page": "directforecast",
      "title": "Function to obtain h-step ahead direct forecast based on estimated VAR, VARX or VARMA model",
      "topics": [
        "directforecast"
      ]
    },
    {
      "page": "fitted.bigtime.VAR",
      "title": "Gives the fitted values of a model estimated using 'sparseVAR'",
      "topics": [
        "fitted.bigtime.VAR"
      ]
    },
    {
      "page": "fitted.bigtime.VARMA",
      "title": "Gives the fitted values of a model estimated using 'sparseVARMA'",
      "topics": [
        "fitted.bigtime.VARMA"
      ]
    },
    {
      "page": "fitted.bigtime.VARX",
      "title": "Gives the fitted values of a model estimated using 'sparseVARX'",
      "topics": [
        "fitted.bigtime.VARX"
      ]
    },
    {
      "page": "get_ic_vals",
      "title": "Calculates the Information Criteria for a VAR, VARX, VARMA model",
      "topics": [
        "get_ic_vals"
      ]
    },
    {
      "page": "get_ic_vals.bigtime.VAR",
      "title": "Calculates the Information Criteria for a model estimated using 'sparseVAR'",
      "topics": [
        "get_ic_vals.bigtime.VAR"
      ]
    },
    {
      "page": "get_ic_vals.bigtime.VARX",
      "title": "Calculates the Information Criteria for a model estimated using 'sparseVARX'",
      "topics": [
        "get_ic_vals.bigtime.VARX"
      ]
    },
    {
      "page": "ic_selection",
      "title": "Selects the optimal penalty parameter using information criteria",
      "topics": [
        "ic_selection"
      ]
    },
    {
      "page": "is.stable",
      "title": "Checks whether a VAR is stable",
      "topics": [
        "is.stable"
      ]
    },
    {
      "page": "lagmatrix",
      "title": "Creates Lagmatrix of Estimated Coefficients",
      "topics": [
        "lagmatrix"
      ]
    },
    {
      "page": "plot_cv",
      "title": "Plot the Cross Validation Error Curve for a Sparse VAR or VARX",
      "topics": [
        "plot_cv"
      ]
    },
    {
      "page": "plot.bigtime.recursiveforecast",
      "title": "Plots Recursive Forecasts",
      "topics": [
        "plot.bigtime.recursiveforecast"
      ]
    },
    {
      "page": "plot.bigtime.simVAR",
      "title": "Plots a simulated VAR",
      "topics": [
        "plot.bigtime.simVAR"
      ]
    },
    {
      "page": "recursiveforecast",
      "title": "Recursively Forecasts a VAR",
      "topics": [
        "recursiveforecast"
      ]
    },
    {
      "page": "residuals.bigtime.VAR",
      "title": "Gives the residuals for VAR models estimated using 'sparseVAR'",
      "topics": [
        "residuals.bigtime.VAR"
      ]
    },
    {
      "page": "residuals.bigtime.VARMA",
      "title": "Gives the residuals for VARMA models estimated using 'sparseVARMA'",
      "topics": [
        "residuals.bigtime.VARMA"
      ]
    },
    {
      "page": "residuals.bigtime.VARX",
      "title": "Gives the residuals for VARX models estimated using 'sparseVARX'",
      "topics": [
        "residuals.bigtime.VARX"
      ]
    },
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      "page": "simVAR",
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      "topics": [
        "simVAR"
      ]
    },
    {
      "page": "sparseVAR",
      "title": "Sparse Estimation of the Vector AutoRegressive (VAR) Model",
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        "sparseVAR"
      ]
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        "sparseVARMA"
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    },
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      "page": "sparseVARX",
      "title": "Sparse Estimation of the Vector AutoRegressive with Exogenous Variables X (VARX) Model",
      "topics": [
        "sparseVARX"
      ]
    },
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      "page": "summary.bigtime.simVAR",
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        "summary.bigtime.simVAR"
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    },
    {
      "page": "X.varx",
      "title": "VARX Time Series Example ('varx.example')",
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      "title": "VARX Time Series Example ('varx.example')",
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