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  "Title": "Simplicial Generalized Beta Regression",
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  "Date": "2020-02-05",
  "Author": "Monique Graf",
  "Maintainer": "Monique Graf <monique.p.n.graf@bluewin.ch>",
  "Description": "Main properties and regression procedures using a\ngeneralization of the Dirichlet distribution called Simplicial\nGeneralized Beta distribution. It is a new distribution on the\nsimplex (i.e. on the space of compositions or positive vectors\nwith sum of components equal to 1). The Dirichlet distribution\ncan be constructed from a random vector of independent Gamma\nvariables divided by their sum. The SGB follows the same\nconstruction with generalized Gamma instead of Gamma variables.\nThe Dirichlet exponents are supplemented by an overall shape\nparameter and a vector of scales. The scale vector is itself a\ncomposition and can be modeled with auxiliary variables through\na log-ratio transformation. Graf, M. (2017, ISBN:\n978-84-947240-0-8). See also the vignette enclosed in the\npackage.",
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  "Date/Publication": "2023-12-07 02:39:23 UTC",
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      "page": "SGB-package",
      "title": "Package SGB",
      "topics": [
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        "SGB"
      ]
    },
    {
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      "title": "arc dataset",
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      ]
    },
    {
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      ]
    },
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    },
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        "rggamma"
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    },
    {
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      "topics": [
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        "GoodnessFit",
        "ks.SGB",
        "print.testSGB"
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    },
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        "initpar.SGB"
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    },
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