Spatial point pattern test for areal data.
sppt compares spatial distributions of events aggregated
to areal units, such as crimes counted by census tract.
sppt() compares two patterns unit by unit with bounded
Monte Carlo bootstrap p-values, and summarises the map with the robust S
index, a sameness test and a test of the spatial arrangement of the
differences.sppt_longitudinal() compares every period of a time
series with the first and classifies each unit’s trajectory.sppt_sameness() tests an S index against sameness.sppt_map() redraws the maps from either analysis with a
chosen layout.install.packages("sppt")library(sppt)
res <- sppt(vancouver_ct, group_col = "id",
count_col = c("BNER2003", "BNER2025"), seed = 42)
summary(res)
sppt_map(res, "pvalue", legend_position = "right")
long <- sppt_longitudinal(vancouver_ct, group_col = "id",
count_col = paste0("BNER", 2003:2025), seed = 42)See vignette("sppt") and
vignette("sppt_longitudinal").
Andresen, M.A. (2009). Testing for similarity in area-based spatial patterns: A nonparametric Monte Carlo approach. Applied Geography, 29(3), 333-345. https://doi.org/10.1016/j.apgeog.2008.12.004
Andresen, M.A. (2016). An area-based nonparametric spatial point pattern test: The test, its applications, and the future. Methodological Innovations, 9, Article 12. https://doi.org/10.1177/2059799116630659
Andresen, M.A. (2026). Testing longitudinal change in spatial distributions and patterns: An extension of the spatial point pattern test. Annals of the American Association of Geographers, in press.