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  "Title": "Multivariate Quantile-on-Quantile Regression",
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  "Authors@R": "c(\nperson(\"Merwan\", \"Roudane\",\nemail = \"merwanroudane920@gmail.com\",\nrole = c(\"aut\", \"cre\", \"cph\")),\nperson(\"Avik\", \"Sinha\", role = \"ctb\",\ncomment = \"Original m-QQR methodology\"),\nperson(\"Nicholas\", \"Sim\", role = \"ctb\",\ncomment = \"Original QQ regression methodology\"),\nperson(\"Hongtao\", \"Zhou\", role = \"ctb\",\ncomment = \"Original QQ regression methodology\"))",
  "Description": "Implements Multivariate Quantile-on-Quantile Regression\n(m-QQR) of Sinha, Ghosh, Hussain, Nguyen and Das (2023)\n<doi:10.1016/j.eneco.2023.107021>, extending the bivariate\nQuantile-on-Quantile regression of Sim and Zhou (2015)\n<doi:10.1016/j.jbankfin.2015.01.013> to include exogenous\nmoderators and controls with optional interaction terms. For\neach pair of quantile levels (theta of the response and tau of\nthe regressor) the package fits a locally-weighted quantile\nregression of y on the principal regressor x, a lagged\ndependent variable, moderators Z and the x*Z interaction terms,\nusing Gaussian kernel weights on the empirical cumulative\ndistribution function (CDF) distance. Bootstrap standard errors\nand Koenker-Machado pseudo R-squared are reported.\nVisualisations include 'MATLAB'-style 'Parula' and 'Jet' 3D\nsurfaces, heatmaps and contour plots through 'plotly'.",
  "License": "GPL-3",
  "Encoding": "UTF-8",
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  "URL": "https://github.com/merwanroudane/multiqqr",
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  "Repository": "https://merwanroudane.r-universe.dev",
  "Date/Publication": "2026-06-01 18:26:26 UTC",
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    "User": "root"
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  "Author": "Merwan Roudane [aut, cre, cph],\nAvik Sinha [ctb] (Original m-QQR methodology),\nNicholas Sim [ctb] (Original QQ regression methodology),\nHongtao Zhou [ctb] (Original QQ regression methodology)",
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  "_created": "2026-10-30T09:18:51.000Z",
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      "page": "mqqr-package",
      "title": "mqqr: Multivariate Quantile-on-Quantile Regression",
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        "mqqr-package",
        "mqqr"
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      "title": "Multivariate Quantile-on-Quantile Regression",
      "topics": [
        "mqq_regression"
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