Moran's I and LISA cluster map for an interpolated variable

Computes global Moran's I and optionally maps Local Indicators of Spatial Association (LISA) clusters for an interpolated variable.

Usage

plot_moran(
  result,
  variable = NULL,
  type = c("lisa", "moran"),
  quantity = "pct_tract",
  significance = 0.05,
  nsim = 999L,
  ...
)

result: An interpElections_result object.
variable: Variable to analyze. Accepts column name, ballot number, candidate name, or party abbreviation.
type: Character. "moran" for the Moran scatterplot, or "lisa" for the LISA cluster map. Default: "lisa".
quantity: Quantity to analyze: "pct_tract" (default), "absolute", "pct_muni", "pct_valid", "pct_eligible", "density". The default "pct_tract" divides raw vote counts by tract turnout, revealing political preference patterns rather than population density patterns. Matches the default of plot.interpElections_result().
significance: Significance level for LISA. Default: 0.05.
nsim: Number of permutations for LISA significance testing (conditional permutation test via spdep::localmoran_perm()). Default: 999. Only used when type = "lisa".
...: Ignored.

A ggplot object (invisibly).