Compute Local Moran's I

Compute Local Moran's I for each observation using either an sf object, a zero-indexed adjacency list, or a spatial weights matrix.

Usage

local_morans(shp, adj, wts, spatial_mat, epsg = 3857)

Arguments

shp

sf dataframe. Optional if adj or spatial_mat is supplied.

adj

Zero-indexed adjacency list. Optional if shp or spatial_mat is supplied.

wts

Numeric vector of observed values.

spatial_mat

Square spatial weights matrix. Optional if shp or adj is supplied.

epsg

numeric EPSG code to planarize to. Default is 3857.

Value

tibble with columns moran, expectation, and variance

Examples

library(dplyr)
data('checkerboard')
checkerboard <- checkerboard |> mutate(m = as.numeric((id + i) %% 2 == 0))
local_morans(shp = checkerboard, wts = checkerboard$m)
#> Warning: Planarizing skipped. `x` missing CRS.
#> # A tibble: 64 × 3
#>    moran expectation variance
#>    <dbl>       <dbl>    <dbl>
#>  1    -2     -0.0317     1.97
#>  2    -3     -0.0476     2.90
#>  3    -3     -0.0476     2.90
#>  4    -3     -0.0476     2.90
#>  5    -3     -0.0476     2.90
#>  6    -3     -0.0476     2.90
#>  7    -3     -0.0476     2.90
#>  8    -2     -0.0317     1.97
#>  9    -3     -0.0476     2.90
#> 10    -4     -0.0635     3.81
#> # ℹ 54 more rows