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  "Title": "Likelihood-Based Intrinsic Dimension Estimators",
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  "Authors@R": "c(\nperson(\"Francesco\", \"Denti\", ,\"francescodenti.personal@gmail.com\",\nrole = c(\"aut\", \"cre\", \"cph\"),\ncomment = c(ORCID = \"0000-0003-2978-4702\")),\nperson(\"Andrea\", \"Gilardi\", ,\"andrea.gilardi@unimib.it\",\nrole = \"aut\",\ncomment = c(ORCID = \"0000-0002-9424-7439\"))\n)",
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  "Description": "Provides functions to estimate the intrinsic dimension of\na dataset via likelihood-based approaches. Specifically, the\npackage implements the 'TWO-NN' and 'Gride' estimators and the\n'Hidalgo' Bayesian mixture model. In addition, the first\nreference contains an extended vignette on the usage of the\n'TWO-NN' and 'Hidalgo' models. References: Denti (2023,\n<doi:10.18637/jss.v106.i09>); Allegra et al. (2020,\n<doi:10.1038/s41598-020-72222-0>); Denti et al. (2022,\n<doi:10.1038/s41598-022-20991-1>); Facco et al. (2017,\n<doi:10.1038/s41598-017-11873-y>); Santos-Fernandez et al.\n(2021, <doi:10.1038/s41598-022-20991-1>).",
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  "URL": "https://github.com/Fradenti/intRinsic",
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      "title": "Plot the simulated MCMC chains for the Bayesian 'Gride'",
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      "topics": [
        "autoplot.gride_bayes"
      ]
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      "topics": [
        "autoplot.gride_evolution"
      ]
    },
    {
      "page": "autoplot.gride_mle",
      "title": "Plot the simulated bootstrap sample for the MLE 'Gride'",
      "topics": [
        "autoplot.gride_mle"
      ]
    },
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      "page": "autoplot.Hidalgo",
      "title": "Plot the output of the 'Hidalgo' function",
      "concept": [
        "autoplot methods"
      ],
      "topics": [
        "autoplot.Hidalgo"
      ]
    },
    {
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      "concept": [
        "autoplot methods"
      ],
      "topics": [
        "autoplot.twonn_bayes"
      ]
    },
    {
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      "concept": [
        "autoplot methods"
      ],
      "topics": [
        "autoplot.twonn_linfit"
      ]
    },
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      "page": "autoplot.twonn_mle",
      "title": "Plot the output of the 'TWO-NN' model estimated via the Maximum Likelihood approach",
      "concept": [
        "autoplot methods"
      ],
      "topics": [
        "autoplot.twonn_mle"
      ]
    },
    {
      "page": "auxHidalgo",
      "title": "Auxiliary functions for the 'Hidalgo' model",
      "topics": [
        "auxHidalgo",
        "credible_intervals",
        "initial_values",
        "posterior_means",
        "posterior_medians"
      ]
    },
    {
      "page": "clustering",
      "title": "Posterior similarity matrix and partition estimation",
      "topics": [
        "clustering",
        "plot.hidalgo_psm",
        "print.hidalgo_psm"
      ]
    },
    {
      "page": "compute_mus",
      "title": "Compute the ratio statistics needed for the intrinsic dimension estimation",
      "topics": [
        "compute_mus",
        "plot.mus",
        "print.mus",
        "print.mus_Nq"
      ]
    },
    {
      "page": "generalized_ratios_distribution",
      "title": "The Generalized Ratio distribution",
      "topics": [
        "dgera",
        "generalized_ratios_distribution",
        "rgera"
      ]
    },
    {
      "page": "gride",
      "title": "'Gride': the Generalized Ratios ID Estimator",
      "topics": [
        "gride",
        "plot.gride_bayes",
        "plot.gride_mle",
        "print.gride_bayes",
        "print.gride_mle",
        "print.summary.gride_bayes",
        "print.summary.gride_mle",
        "summary.gride_bayes",
        "summary.gride_mle"
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        "print.gride_evolution"
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        "plot.Hidalgo",
        "print.Hidalgo",
        "print.summary.Hidalgo",
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