{
  "_id": "6a0f6e7eacfb0bcc41c5eeea",
  "Package": "timevarcorr",
  "Title": "Time Varying Correlation",
  "Version": "0.1.1.9000",
  "Authors@R": "c(person(\"Alexandre\", \"Courtiol\", email = \"alexandre.courtiol@gmail.com\", role = c(\"aut\", \"cre\", \"cph\"), comment = c(ORCID = \"0000-0003-0637-2959\")),\nperson(\"François\", \"Rousset\", role = \"aut\", comment = c(ORCID = \"0000-0003-4670-0371\")))",
  "Description": "Computes how the correlation between 2 time-series changes\nover time. To do so, the package follows the method from Choi &\nShin (2021) <doi:10.1007/s42952-020-00073-6>. It performs a\nnon-parametric kernel smoothing (using a common bandwidth) of\nall underlying components required for the computation of a\ncorrelation coefficient (i.e., x, y, x^2, y^2, xy). An\nautomatic selection procedure for the bandwidth parameter is\nimplemented. Alternative kernels can be used (Epanechnikov, box\nand normal). Both Pearson and Spearman correlation coefficients\ncan be estimated and change in correlation over time can be\ntested.",
  "License": "MIT + file LICENSE",
  "Encoding": "UTF-8",
  "Roxygen": "list(markdown = TRUE)",
  "RoxygenNote": "7.2.3",
  "LazyData": "true",
  "Language": "en-US",
  "URL": "https://courtiol.github.io/timevarcorr/,\nhttps://github.com/courtiol/timevarcorr",
  "BugReports": "https://github.com/courtiol/timevarcorr/issues",
  "Config/testthat/edition": "3",
  "Repository": "https://courtiol.r-universe.dev",
  "Date/Publication": "2023-11-07 20:02:24 UTC",
  "RemoteUrl": "https://github.com/courtiol/timevarcorr",
  "RemoteRef": "HEAD",
  "RemoteSha": "074663dbd83ddeb873480dd266bce51989712ae7",
  "NeedsCompilation": "no",
  "Packaged": {
    "Date": "2026-05-21 07:53:51 UTC",
    "User": "root"
  },
  "Author": "Alexandre Courtiol [aut, cre, cph] (ORCID:\n<https://orcid.org/0000-0003-0637-2959>),\nFrançois Rousset [aut] (ORCID: <https://orcid.org/0000-0003-4670-0371>)",
  "Maintainer": "Alexandre Courtiol <alexandre.courtiol@gmail.com>",
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  "_user": "courtiol",
  "_type": "src",
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  "_created": "2026-05-21T07:53:51.000Z",
  "_published": "2026-05-21T20:43:42.552Z",
  "_distro": "noble",
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    "author": "Alexandre Courtiol <alexandre.courtiol@gmail.com>",
    "committer": "Alexandre Courtiol <alexandre.courtiol@gmail.com>",
    "message": "New devel version\n",
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    "email": "alexandre.courtiol@gmail.com",
    "login": "courtiol",
    "linkedin": "in/alexandre-courtiol-538b5a185",
    "orcid": "0000-0003-0637-2959",
    "twitter": "@rdataberlin",
    "description": "Quantitative wildlife biologist at Leibniz-IZW Berlin / Rstats lecturer at FU Berlin / Rstats consultant. R & LaTeX fulfill 99% of my coding needs!",
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  "_stars": 1,
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  "_assets": [
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    "extra/citation.html",
    "extra/citation.json",
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  "_realowner": "courtiol",
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    "calc_Gamma",
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    "calc_L_And",
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    "calc_RMSE",
    "calc_SE",
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      "name": "stockprice",
      "title": "Daily Closing Prices of Major European Stock Indices, April 2000-December 2017",
      "object": "stockprice",
      "class": [
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        "tbl",
        "data.frame"
      ],
      "fields": [
        "DateID",
        "SP500",
        "FTSE100",
        "Nikkei",
        "DAX",
        "NASDAQ",
        "Event"
      ],
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      "table": true,
      "tojson": true
    }
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    {
      "page": "dot-onAttach",
      "title": "Display welcome message",
      "topics": [
        ".onAttach"
      ]
    },
    {
      "page": "CI",
      "title": "Internal functions for the computation of confidence intervals",
      "topics": [
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        "calc_e",
        "calc_Gamma",
        "calc_GammaINF",
        "calc_H",
        "calc_L_And",
        "calc_SE",
        "CI"
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      "title": "Determine if the package is being used by pkgdown",
      "topics": [
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    },
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      "title": "Smoothing by kernel regression",
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    },
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      "title": "Daily Closing Prices of Major European Stock Indices, April 2000-December 2017",
      "topics": [
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    },
    {
      "page": "tcor",
      "title": "Compute time varying correlation coefficients",
      "topics": [
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        "calc_RMSE",
        "select_h",
        "tcor"
      ]
    },
    {
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      "title": "Compute equality test between correlation coefficient estimates at two time points",
      "topics": [
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      ]
    },
    {
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      "title": "Test difference between correlation coefficient estimates and a value of reference",
      "topics": [
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      ]
    }
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