{
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  "Package": "quollr",
  "Title": "Visualising How Nonlinear Dimension Reduction Warps Your Data",
  "Version": "1.0.6",
  "Authors@R": "c(\nperson(\"Jayani P.\", \"Gamage\", , \"jayanilakshika76@gmail.com\", role = c(\"aut\", \"cre\"),\ncomment = c(ORCID = \"0000-0002-6265-6481\")),\nperson(\"Dianne\", \"Cook\", , \"dicook@monash.edu\", role = \"aut\",\ncomment = c(ORCID = \"0000-0002-3813-7155\")),\nperson(\"Paul\", \"Harrison\", , \"paul.harrison@monash.edu\", role = \"aut\",\ncomment = c(ORCID = \"0000-0002-3980-268X\")),\nperson(\"Michael\", \"Lydeamore\", , \"michael.lydeamore@monash.edu\", role = \"aut\",\ncomment = c(ORCID = \"0000-0001-6515-827X\")),\nperson(\"Thiyanga S.\", \"Talagala\", , \"ttalagala@sjp.ac.lk\", role = \"aut\",\ncomment = c(ORCID = \"0000-0002-0656-9789\"))\n)",
  "Description": "To construct a model in 2-D space from 2-D nonlinear\ndimension reduction data and then lift it to the\nhigh-dimensional space. Additionally, provides tools to\nvisualise the model overlay the data in 2-D and\nhigh-dimensional space. Furthermore, provides summaries and\ndiagnostics to evaluate the nonlinear dimension reduction\nlayout.",
  "License": "MIT + file LICENSE",
  "URL": "https://jayanilakshika.github.io/quollr/",
  "BugReports": "https://github.com/jayanilakshika/quollr/issues",
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  "Repository": "https://jayanilakshika.r-universe.dev",
  "Date/Publication": "2026-06-09 06:08:50 UTC",
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  "Author": "Jayani P. Gamage [aut, cre] (ORCID:\n<https://orcid.org/0000-0002-6265-6481>),\nDianne Cook [aut] (ORCID: <https://orcid.org/0000-0002-3813-7155>),\nPaul Harrison [aut] (ORCID: <https://orcid.org/0000-0002-3980-268X>),\nMichael Lydeamore [aut] (ORCID:\n<https://orcid.org/0000-0001-6515-827X>),\nThiyanga S. Talagala [aut] (ORCID:\n<https://orcid.org/0000-0002-0656-9789>)",
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    "comb_all_data_model_error",
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    "fit_highd_model",
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    "gen_hex_coord",
    "gen_scaled_data",
    "geom_hexgrid",
    "geom_trimesh",
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    "glance",
    "group_hex_pts",
    "hex_binning",
    "merge_hexbin_centroids",
    "merge_hexbin_mean",
    "plot_hbe_layouts",
    "plot_proj",
    "predict_emb",
    "quad",
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    "show_langevitour",
    "show_link_plots",
    "stat_hexgrid",
    "stat_trimesh",
    "tri_bin_centroids",
    "update_trimesh_index"
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      "object": "scurve_model_obj",
      "class": [
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      "fields": [],
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      "page": "assign_data",
      "title": "Assign data to hexagons",
      "topics": [
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      "page": "augment",
      "title": "S3 generic for augment",
      "topics": [
        "augment"
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      "title": "Augment Data with Predictions and Error Metrics for NLDR Models",
      "topics": [
        "augment.highd_vis_model"
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    {
      "page": "avg_highD_data",
      "title": "Create a tibble with averaged high-dimensional data",
      "topics": [
        "avg_highd_data"
      ]
    },
    {
      "page": "calc_2d_dist",
      "title": "Calculate 2-D Euclidean distances between vertices",
      "topics": [
        "calc_2d_dist"
      ]
    },
    {
      "page": "calc_bins_y",
      "title": "Calculate the effective number of bins along x-axis and y-axis",
      "topics": [
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      ]
    },
    {
      "page": "comb_all_data_model",
      "title": "Create a tibble with averaged high-dimensional data and high-dimensional data, non-linear dimension reduction data",
      "topics": [
        "comb_all_data_model"
      ]
    },
    {
      "page": "comb_all_data_model_error",
      "title": "Create a tibble with averaged high-dimensional data and high-dimensional data, non-linear dimension reduction data, model error data",
      "topics": [
        "comb_all_data_model_error"
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    },
    {
      "page": "comb_data_model",
      "title": "Create a tibble with averaged high-dimensional data and high-dimensional data",
      "topics": [
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      ]
    },
    {
      "page": "compute_mean_density_hex",
      "title": "Compute mean density of hexagonal bins",
      "topics": [
        "compute_mean_density_hex"
      ]
    },
    {
      "page": "compute_std_counts",
      "title": "Compute standardise counts in hexagons",
      "topics": [
        "compute_std_counts"
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    },
    {
      "page": "find_low_dens_hex",
      "title": "Find low-density Hexagons",
      "topics": [
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      ]
    },
    {
      "page": "find_non_empty_bins",
      "title": "Find the number of bins required to achieve required number of non-empty bins.",
      "topics": [
        "find_non_empty_bins"
      ]
    },
    {
      "page": "fit_highd_model",
      "title": "Construct the 2-D model and lift into high-dimensions",
      "topics": [
        "fit_highd_model"
      ]
    },
    {
      "page": "gen_axes",
      "title": "Generate Axes for Projection",
      "topics": [
        "gen_axes"
      ]
    },
    {
      "page": "gen_centroids",
      "title": "Generate centroid coordinate",
      "topics": [
        "gen_centroids"
      ]
    },
    {
      "page": "gen_design",
      "title": "Generate a design to layout 2-D representations",
      "topics": [
        "gen_design"
      ]
    },
    {
      "page": "gen_diffbin1_errors",
      "title": "Generate erros and MSE for different bin widths",
      "topics": [
        "gen_diffbin1_errors"
      ]
    },
    {
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