{
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  "Title": "Tree-Spatial Scan Statistic for Cluster Detection",
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  "Authors@R": "c(\nperson(\"Allan\", \"Quadros\", email = \"allanvcq@gmail.com\",\nrole = c(\"aut\", \"cre\"),\ncomment = c(ORCID = \"0000-0003-3250-5380\")),\nperson(\"Andre L. F.\", \"Cançado\",\nrole = \"aut\",\ncomment = c(ORCID = \"0000-0002-7019-8521\"))\n)",
  "Description": "Implements the tree-spatial scan statistic for detecting\nclusters that combine both spatial and hierarchical structures,\nas proposed by Cancado et al. (2025)\n<doi:10.1007/s10651-025-00670-w>. The method extends Kulldorff\n(1997) <doi:10.1080/03610929708831995> circular spatial scan\nstatistic and the tree-based scan statistic of Kulldorff et al.\n(2003) <doi:10.1111/1541-0420.00039> by searching for anomalies\nin both geographic regions and branches of hierarchical trees\nsimultaneously. The package also provides standalone\nimplementations of Kulldorff's circular spatial scan statistic\nand the tree-based scan statistic. Statistical significance is\nassessed via Monte Carlo simulation under a Poisson or binomial\nmodel, with optional 'OpenMP' parallelization.",
  "License": "GPL (>= 3)",
  "URL": "https://github.com/allanvc/treeSS",
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  "Author": "Allan Quadros [aut, cre] (ORCID:\n<https://orcid.org/0000-0003-3250-5380>), Andre L. F. Cançado\n[aut] (ORCID: <https://orcid.org/0000-0002-7019-8521>)",
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    {
      "page": "treeSS-package",
      "title": "treeSS: Tree-Spatial Scan Statistic for Cluster Detection",
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        "treeSS-package",
        "treeSS"
      ]
    },
    {
      "page": "aggregate_tree",
      "title": "Aggregate Case Counts from Leaves to All Nodes in a Hierarchical Tree",
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      "title": "Build Candidate Spatial Zones Using Circular Windows",
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      "title": "Chicago Crime (2023)",
      "topics": [
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      "title": "Chicago Community Area Boundaries",
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    {
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      "title": "Kulldorff's Circular Spatial Scan Statistic",
      "topics": [
        "circular_scan"
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    {
      "page": "filter_clusters",
      "title": "Filter Overlapping Secondary Clusters",
      "topics": [
        "filter_clusters",
        "filter_clusters.circular_scan",
        "filter_clusters.default",
        "filter_clusters.treespatial_scan",
        "filter_clusters.tree_scan"
      ]
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    {
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      "title": "Florida General Mortality Data (2016)",
      "topics": [
        "fl_deaths"
      ]
    },
    {
      "page": "generate_example_data",
      "title": "Generate Example Data for Tree-Spatial Scan",
      "topics": [
        "generate_example_data"
      ]
    },
    {
      "page": "get_cluster_regions",
      "title": "Extract Cluster Membership for Each Region",
      "topics": [
        "get_cluster_regions",
        "get_cluster_regions.default",
        "get_cluster_regions.sequential_scan"
      ]
    },
    {
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      "title": "London Borough Boundaries",
      "topics": [
        "london_boroughs_map"
      ]
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    {
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      "title": "London Road Collisions (2022)",
      "topics": [
        "london_collisions"
      ]
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      "title": "London Road Collisions - Hierarchy",
      "topics": [
        "london_tree"
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    },
    {
      "page": "most_likely_cluster",
      "title": "Extract the Most Likely Cluster from a Scan Result",
      "topics": [
        "most_likely_cluster",
        "most_likely_cluster.sequential_scan",
        "most_likely_cluster.treess"
      ]
    },
    {
      "page": "plot.tree_scan",
      "title": "Plot the Top Tree Cuts of a Tree-Only Scan",
      "topics": [
        "plot.tree_scan"
      ]
    },
    {
      "page": "plot.treess",
      "title": "Plot the Clusters Detected by a Scan",
      "topics": [
        "plot.treess"
      ]
    },
    {
      "page": "print.circular_scan",
      "title": "Print Method for circular_scan Objects",
      "topics": [
        "print.circular_scan"
      ]
    },
    {
      "page": "print.sequential_scan",
      "title": "Print Method for sequential_scan Objects",
      "topics": [
        "print.sequential_scan"
      ]
    },
    {
      "page": "print.tree_scan",
      "title": "Print Method for tree_scan Objects",
      "topics": [
        "print.tree_scan"
      ]
    },
    {
      "page": "print.treespatial_scan",
      "title": "Print Method for treespatial_scan Objects",
      "topics": [
        "print.treespatial_scan"
      ]
    },
    {
      "page": "pvalue",
      "title": "Extract the Monte Carlo P-Value from a Scan Result",
      "topics": [
        "pvalue",
        "pvalue.sequential_scan",
        "pvalue.treess"
      ]
    },
    {
      "page": "rj_map",
      "title": "Rio de Janeiro Municipal Boundaries",
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        "rj_map"
      ]
    },
    {
      "page": "rj_mortality",
      "title": "Rio de Janeiro Infant Mortality (2016)",
      "topics": [
        "rj_mortality"
      ]
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    {
      "page": "rj_tree",
      "title": "Rio de Janeiro Infant Mortality - ICD-10 Tree",
      "topics": [
        "rj_tree"
      ]
    },
    {
      "page": "secondary_clusters",
      "title": "Extract Secondary Clusters from a Scan Result",
      "topics": [
        "secondary_clusters",
        "secondary_clusters.sequential_scan",
        "secondary_clusters.treess",
        "secondary_clusters.tree_scan"
      ]
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    {
      "page": "sequential_scan",
      "title": "Sequential Scan for Secondary Clusters",
      "topics": [
        "sequential_scan"
      ]
    },
    {
      "page": "summary.circular_scan",
      "title": "Summary Method for circular_scan Objects",
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        "summary.circular_scan"
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      "title": "Summary Method for sequential_scan Objects",
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      "title": "Summary Method for tree_scan Objects",
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      "title": "Summary Method for treespatial_scan Objects",
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      "title": "Tree-Based Scan Statistic",
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      "title": "Tree-Spatial Scan Statistic",
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      ]
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      "title": "Building treeSS inputs from raw data: Florida mortality 2016",
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      "headings": [
        "What this vignette adds",
        "1. Load the raw data",
        "2. Build the ICD-10 tree from the codes in the data",
        "3. Download polygons and centroids",
        "4. Assemble the long-format data.frame",
        "5. Run the tree-spatial scan",
        "6. Distinct secondary clusters (paper-faithful)",
        "7. Sequential scan when the MLC may shadow",
        "8. Visualize the clusters",
        "Recap",
        "References"
      ],
      "created": "2026-05-30 04:31:00",
      "modified": "2026-10-02 18:33:39",
      "commits": 3
    },
    {
      "source": "introduction.Rmd",
      "filename": "introduction.html",
      "title": "Introduction to treeSS: reproducing Cançado et al. (2025)",
      "engine": "knitr::rmarkdown",
      "headings": [
        "Overview",
        "Infant mortality in Rio de Janeiro",
        "Run the scan",
        "Why the joint scan matters here",
        "Multiple distinct clusters (paper-faithful)",
        "Visualizing the cluster",
        "Secondary clusters when the MLC shadows weaker ones",
        "When to use which",
        "Computational notes",
        "Other examples shipped with the package",
        "References"
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      "created": "2026-05-15 21:32:39",
      "modified": "2026-10-02 18:33:39",
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