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Map LISA clusters

Source: R/spatial-stats.R
lisa_map.Rd

The map of local_morans(): countries coloured by cluster type, with non-significant ones left neutral. Hot spots (High-High) and cold spots (Low-Low) read immediately; the off-diagonal categories are the spatial outliers.

Usage

lisa_map(
  data,
  value,
  weights = NULL,
  n_perm = 9999,
  alpha = 0.05,
  p_adjust = c("fdr", "bonferroni", "holm", "none"),
  ...
)

Arguments

data

A map-ready frame (polygon or sf) with iso3c.

value

The value column (unquoted).

weights

A country_weights() object; NULL (default) is country_weights("knn", k = 5), as in local_morans().

n_perm, alpha, p_adjust

Passed to local_morans(). The significance mask uses the adjusted p-values, and the caption names the method.

...

Passed to world_map().

Value

A ggplot object, with the local_morans() table attached as the "countryatlas_lisa" attribute.

Backend

Either backend, as world_map(): the frame decides, and both draw in Equal Earth unless projection is passed on through ....

See also

local_morans(), morans_i()

Examples

# \donttest{
snap <- countryatlas::world_snapshot$countries
set.seed(1)
attach_geometry(snap, geometry = "polygon") |>
  lisa_map(gdp_per_capita, weights = country_weights("knn", k = 5),
           n_perm = 99)

# }