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treeSS

Tree-Spatial Scan Statistic for Cluster Detection

Implements the tree-spatial scan statistic (Cançado et al., 2025), which detects clusters that are anomalous in both geographic space and a hierarchical tree simultaneously. The method searches over circular spatial zones and branches of a classification tree to find regions where observed cases significantly exceed expectations under a Poisson or binomial model, selectable via the model argument.

Installation

# From CRAN (after acceptance)
install.packages("treeSS")

# Development version from GitHub
# install.packages("remotes")
remotes::install_github("allanvc/treeSS")

Quick start

library(treeSS)

# Example: London road collisions
data(london_collisions)
data(london_tree)

# The function takes parallel vectors - extract them from your data.frame
# and pass each one explicitly. This makes the choice of denominator,
# coordinates, etc. transparent.
result <- treespatial_scan(
  cases       = london_collisions$cases,
  population  = london_collisions$population,
  region_id   = london_collisions$region_id,
  x           = london_collisions$x,
  y           = london_collisions$y,
  node_id     = london_collisions$node_id,
  tree        = london_tree,
  nsim        = 999, seed = 42,
  n_cores     = 4L                 # parallelize the MC over 4 threads
)
print(result)

# Extract cluster membership for visualization
cr <- get_cluster_regions(result, n_clusters = 3, overlap = FALSE)

Included datasets

Dataset	Country	Domain	Regions	Tree
`rj_mortality` + `rj_tree`	Brazil	Infant mortality	92 municipalities	ICD-10 (622 nodes)
`fl_deaths`	USA	General mortality	65 counties	raw (built by user)
`london_collisions` + `london_tree`	UK	Road collisions	33 boroughs	Light x Road x Junction (81 nodes)
`chicago_crimes` + `chicago_tree`	USA	Crime	77 community areas	Type x Description x Location (2841 nodes)
`london_boroughs_map`, `chicago_map`		Polygon boundaries		–

Key functions

treespatial_scan() — tree-spatial scan (main function)
circular_scan() — Kulldorff’s spatial scan
tree_scan() — tree-based scan
filter_clusters() — non-overlapping secondary clusters
get_cluster_regions() — cluster membership for any visualization package

Visualization

The package is visualization-agnostic. get_cluster_regions() returns a data.frame that can be merged with any spatial object for plotting with ggplot2, leaflet, tmap, or any other mapping package. See vignette("introduction") for worked examples with ggplot2 + geobr (Brazil), leaflet + tigris (USA), and leaflet + sf (London).

References

Cançado, A. L. F., Oliveira, G. S., Quadros, A. V. C., & Duczmal, L. (2025). A tree-spatial scan statistic. Environmental and Ecological Statistics, 32, 953–978. doi:10.1007/s10651-025-00670-w

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
Health stats visible at Monitor.