{
  "_id": "6a103274acfb0bcc41c9788a",
  "Package": "INFOSET",
  "Type": "Package",
  "Title": "Computing a New Informative Distribution Set of Asset Returns",
  "Version": "4.1.1",
  "Authors@R": "c(person(\"Gloria\", \"Polinesi\", , \"g.polinesi@staff.univpm.it\", role = c(\"aut\", \"cre\")),\nperson(\"Francesca\", \"Mariani\", role = \"aut\"),\nperson(\"Maria Cristina\", \"Recchioni\", role = \"aut\"))",
  "Author": "Gloria Polinesi [aut, cre], Francesca Mariani [aut], Maria\nCristina Recchioni [aut]",
  "Maintainer": "Gloria Polinesi <g.polinesi@staff.univpm.it>",
  "Description": "Estimation of the most-left informative set of gross\nreturns (i.e., the informative set). The procedure to compute\nthe informative set adjusts the method proposed by Mariani et\nal. (2022a) <doi:10.1007/s11205-020-02440-6> and Mariani et al.\n(2022b) <doi:10.1007/s10287-022-00422-2> to gross returns of\nfinancial assets. This is accomplished through an adaptive\nalgorithm that identifies sub-groups of gross returns in each\niteration by approximating their distribution with a sequence\nof two-component log-normal mixtures. These sub-groups emerge\nwhen a significant change in the distribution occurs below the\nmedian of the financial returns, with their boundary termed as\nthe “change point\" of the mixture. The process concludes when\nno further change points are detected. The outcome encompasses\nparameters of the leftmost mixture distributions and change\npoints of the analyzed financial time series. The\nfunctionalities of the INFOSET package include: (i) modelling\nasset distribution detecting the parameters which describe left\ntail behaviour (infoset function), (ii) clustering, (iii)\nlabeling of the financial series for predictive and\nclassification purposes through a Left Risk measure based on\nthe first change point (LR_cp function) (iv) portfolio\nconstruction (ptf_construction function). The package also\nprovide a specific function to construct rolling windows of\ndifferent length size and overlapping time.",
  "License": "GPL (>= 2)",
  "Encoding": "UTF-8",
  "LazyData": "true",
  "RoxygenNote": "7.3.3",
  "Config/testthat/edition": "3",
  "VignetteBuilder": "knitr",
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  "Packaged": {
    "Date": "2026-05-12 08:38:51 UTC",
    "User": "root"
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  "Repository": "https://cran.r-universe.dev",
  "Date/Publication": "2026-02-11 16:32:39 UTC",
  "RemoteUrl": "https://github.com/cran/INFOSET",
  "RemoteRef": "HEAD",
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  "MD5sum": "242f185ea06e01ba97837c27332c067f",
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  "_type": "src",
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  "_created": "2026-05-12T08:38:51.000Z",
  "_published": "2026-05-22T10:39:48.836Z",
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    "id": "5055f4d5319ee10ad64f4b57aa859dde09c2bc58",
    "author": "Gloria Polinesi <g.polinesi@staff.univpm.it>",
    "committer": "cran-robot <csardi.gabor+cran@gmail.com>",
    "message": "version 4.1.1\n",
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  "_maintainer": {
    "name": "Gloria Polinesi",
    "email": "g.polinesi@staff.univpm.it"
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    "name": "cran",
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    "source": "https://cranlogs.r-pkg.org/downloads/total/last-month/INFOSET"
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    "manual.pdf"
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      "date": "2024-11-23"
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  "_exports": [
    "create_overlapping_windows",
    "g_ret",
    "infoset",
    "LR_cp",
    "plot_ptf",
    "ptf_construction",
    "summary_ptf",
    "tail_mixture"
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    {
      "name": "asset.label",
      "title": "Data for clustering and labeling ETFs",
      "object": "asset.label",
      "class": [
        "spec_tbl_df",
        "tbl_df",
        "tbl",
        "data.frame"
      ],
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        "id",
        "label",
        "class"
      ],
      "rows": 44,
      "table": true,
      "tojson": true
    },
    {
      "name": "sample.data",
      "title": "Data for infoset function",
      "object": "sample.data",
      "class": [
        "data.frame"
      ],
      "fields": [
        "ETF_1",
        "ETF_2",
        "ETF_3",
        "ETF_4",
        "ETF_5",
        "ETF_6",
        "ETF_7",
        "ETF_8",
        "ETF_9",
        "ETF_10",
        "ETF_11",
        "ETF_12",
        "ETF_13",
        "ETF_14",
        "ETF_15",
        "ETF_16",
        "ETF_17",
        "ETF_18",
        "ETF_19",
        "ETF_20",
        "ETF_21",
        "ETF_22",
        "ETF_23",
        "ETF_24",
        "ETF_25",
        "ETF_26",
        "ETF_27",
        "ETF_28",
        "ETF_29",
        "ETF_30",
        "ETF_31",
        "ETF_32",
        "ETF_33",
        "ETF_34",
        "ETF_35",
        "ETF_36",
        "ETF_37",
        "ETF_38",
        "ETF_39",
        "ETF_40",
        "ETF_41",
        "ETF_42",
        "ETF_43",
        "ETF_44"
      ],
      "rows": 3174,
      "table": true,
      "tojson": true
    },
    {
      "name": "sample.data.ts",
      "title": "Data with time points for portfolio construction using the LR_cp measure",
      "object": "sample.data.ts",
      "class": [
        "data.frame"
      ],
      "fields": [
        "Date",
        "ETF_1",
        "ETF_2",
        "ETF_3",
        "ETF_4",
        "ETF_5",
        "ETF_6",
        "ETF_7",
        "ETF_8",
        "ETF_9",
        "ETF_10",
        "ETF_11",
        "ETF_12",
        "ETF_13",
        "ETF_14",
        "ETF_15",
        "ETF_16",
        "ETF_17",
        "ETF_18",
        "ETF_19",
        "ETF_20",
        "ETF_21",
        "ETF_22",
        "ETF_23",
        "ETF_24",
        "ETF_25",
        "ETF_26",
        "ETF_27",
        "ETF_28",
        "ETF_29",
        "ETF_30",
        "ETF_31",
        "ETF_32",
        "ETF_33",
        "ETF_34",
        "ETF_35",
        "ETF_36",
        "ETF_37",
        "ETF_38",
        "ETF_39",
        "ETF_40",
        "ETF_41",
        "ETF_42",
        "ETF_43",
        "ETF_44"
      ],
      "rows": 3174,
      "table": true,
      "tojson": true
    }
  ],
  "_help": [
    {
      "page": "asset.label",
      "title": "Data for clustering and labeling ETFs",
      "topics": [
        "asset.label"
      ]
    },
    {
      "page": "create_overlapping_windows",
      "title": "Function to create overlapping windows.",
      "topics": [
        "create_overlapping_windows"
      ]
    },
    {
      "page": "g_ret",
      "title": "Function to compute gross returns.",
      "topics": [
        "g_ret"
      ]
    },
    {
      "page": "infoset",
      "title": "Procedure to find the most-left distribution set.",
      "topics": [
        "infoset"
      ]
    },
    {
      "page": "LR_cp",
      "title": "Function to compute Left risk measure.",
      "topics": [
        "LR_cp"
      ]
    },
    {
      "page": "plot_LR_cp",
      "title": "Plot methods for a LR_cp object",
      "topics": [
        "plot_LR_cp"
      ]
    },
    {
      "page": "plot_ptf",
      "title": "Plot methods for a ptf_construction object",
      "topics": [
        "plot_ptf"
      ]
    },
    {
      "page": "ptf_construction",
      "title": "Function to compute portfolio values",
      "topics": [
        "ptf_construction"
      ]
    },
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      "page": "sample.data",
      "title": "Data for infoset function",
      "topics": [
        "sample.data"
      ]
    },
    {
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      "title": "Data with time points for portfolio construction using the LR_cp measure",
      "topics": [
        "sample.data.ts"
      ]
    },
    {
      "page": "summary_ptf",
      "title": "Plot methods for a ptf_construction object",
      "topics": [
        "summary_ptf"
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      "page": "tail_mixture",
      "title": "Function to find the most-left distribution set.",
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        "tail_mixture"
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      "title": "Vignettes from package 'INFOSET'",
      "author": "Gloria Polinesi",
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