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  "Package": "covsep",
  "Title": "Tests for Determining if the Covariance Structure of\n2-Dimensional Data is Separable",
  "Version": "1.1.1",
  "Authors@R": "c(person(\"Shahin\", \"Tavakoli\", email = \"shahin.tavakoli@unige.ch\", role = c(\"aut\", \"cre\"), comment = c(ORCID = \"0000-0002-6323-6227\")),\nperson(\"Davide\", \"Pigoli\", email = \"davide.pigoli@kcl.ac.uk\", role = c(\"ctb\")),\nperson(\"John\", \"Aston\", email = \"j.aston@statslab.cam.ac.uk\", role = c(\"ctb\")))",
  "Description": "Functions for testing if the covariance structure of\n2-dimensional data (e.g. samples of surfaces X_i = X_i(s,t)) is\nseparable, i.e. if covariance(X) = C_1 x C_2. A complete\ndescriptions of the implemented tests can be found in the paper\nAston et al. (2017) <doi:10.1214/16-AOS1495>\n<doi:10.48550/arXiv.1505.02023>.",
  "Encoding": "UTF-8",
  "License": "GPL-2",
  "LazyData": "true",
  "URL": "https://doi.org/10.1214/16-AOS1495",
  "Config/roxygen2/version": "8.0.0",
  "Repository": "https://stavakol.r-universe.dev",
  "Date/Publication": "2026-06-26 15:54:56 UTC",
  "RemoteUrl": "https://github.com/stavakol/covsep",
  "RemoteRef": "HEAD",
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  "NeedsCompilation": "no",
  "Packaged": {
    "Date": "2026-09-20 10:10:57 UTC",
    "User": "root"
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  "Author": "Shahin Tavakoli [aut, cre] (ORCID:\n<https://orcid.org/0000-0002-6323-6227>),\nDavide Pigoli [ctb],\nJohn Aston [ctb]",
  "Maintainer": "Shahin Tavakoli <shahin.tavakoli@unige.ch>",
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  "_created": "2026-09-20T10:10:57.000Z",
  "_published": "2026-09-20T10:14:07.178Z",
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  "_realowner": "stavakol",
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    "empirical_bootstrap_test",
    "gaussian_bootstrap_test",
    "generate_surface_data",
    "HS_empirical_bootstrap_test",
    "HS_gaussian_bootstrap_test",
    "marginal_covariances",
    "projected_differences",
    "renormalize_mtnorm",
    "rmtnorm"
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      "name": "C1",
      "title": "A covariance matrix",
      "object": "C1",
      "class": [
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        "array"
      ],
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      "rows": 32,
      "table": true,
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    },
    {
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      "title": "A covariance matrix",
      "object": "C2",
      "class": [
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        "array"
      ],
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      "rows": 7,
      "table": true,
      "tojson": true
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      "object": "SurfacesData",
      "class": [
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      "table": false,
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  "_help": [
    {
      "page": "C1",
      "title": "A covariance matrix",
      "topics": [
        "C1"
      ]
    },
    {
      "page": "C2",
      "title": "A covariance matrix",
      "topics": [
        "C2"
      ]
    },
    {
      "page": "clt_test",
      "title": "Test for separability of covariance operators for Gaussian process.",
      "topics": [
        "clt_test"
      ]
    },
    {
      "page": "covsep",
      "title": "covsep: tests for determining if the covariance structure of 2-dimensional data is separable",
      "topics": [
        "covsep-package",
        "covsep"
      ]
    },
    {
      "page": "difference_fullcov",
      "title": "compute the difference between the full sample covariance and its separable approximation",
      "topics": [
        "difference_fullcov"
      ]
    },
    {
      "page": "empirical_bootstrap_test",
      "title": "Projection-based empirical bootstrap test for separability of covariance structure",
      "topics": [
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      ]
    },
    {
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    },
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      "page": "generate_surface_data",
      "title": "Generate surface data",
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      "page": "HS_empirical_bootstrap_test",
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      "topics": [
        "HS_gaussian_bootstrap_test"
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    },
    {
      "page": "marginal_covariances",
      "title": "estimates marginal covariances (e.g. row and column covariances) of bi-dimensional sample",
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        "marginal_covariances"
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    },
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      "title": "Generate a sample from a Matrix Gaussian distribution",
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