Local Neighbor Match Test — nb_match

Implements the Local Neighbor Match Test as described in Tobler's Law in a Multivariate World (Anselin and Li, 2020).

Usage

nb_match_test(
  x,
  nb,
  wt = st_weights(nb),
  k = 10,
  nsim = 499,
  scale = TRUE,
  .method = "euclidian",
  .p = 2
)

Arguments

x: a numeric vector or a list of numeric vectors of equal length.
nb: a neighbor list object for example as created by st_contiguity().
wt: a weights list as created by st_weights().
k: the number of neighbors to identify in attribute space. Should be the same as number of neighbors provided in st_knn.
nsim: the number of simulations to run for calculating the simulated p-value.
scale: default TRUE. Whether x should be scaled or not. Note that measures should be standardized.
.method: default "euclidian". The distance measure passed to stats::dist().
.p: default 2. The power of Minkowski distance passed to the p argument in stats::dist().

Value

a data.frame with columns

n_shared (integer): the number of shared neighbors between geographic and attribute space
nb_matches (list): matched neighbor indexes. Each element is an integer vector of same length as the ith observation of n_shared
knn_nb (list): the neighbors in attribute space
probability (numeric): the geometric probability of observing the number of matches
p_sim (numeric): a folded simulated p-value

Examples


if (requireNamespace("dplyr", quietly = TRUE)) {
library(magrittr)
guerry %>%
  dplyr::transmute(nb = st_knn(geometry, k = 10),
         nmt = nb_match_test(list(crime_pers, literacy, suicides),
                             nb, nsim = 999)) %>%
  tidyr::unnest(nmt)
 }
#> ! Polygon provided. Using point on surface.
#> Simple feature collection with 85 features and 6 fields
#> Geometry type: MULTIPOLYGON
#> Dimension:     XY
#> Bounding box:  xmin: 47680 ymin: 1703258 xmax: 1031401 ymax: 2677441
#> CRS:           NA
#> # A tibble: 85 × 7
#>    nb    n_shared nb_matches knn_nb probability p_sim                   geometry
#>    <nb>     <int> <list>     <list>       <dbl> <dbl>             <MULTIPOLYGON>
#>  1 <int>        1 <int [1]>  <int>      0.400   0.671 (((801150 2092615, 800669…
#>  2 <int>        3 <int [3]>  <int>      0.0782  0.096 (((729326 2521619, 729320…
#>  3 <int>        5 <int [5]>  <int>      0.00147 0.003 (((710830 2137350, 711746…
#>  4 <int>        4 <int [4]>  <int>      0.0141  0.018 (((882701 1920024, 882408…
#>  5 <int>        0 <int [0]>  <int>      0.260   0.262 (((886504 1922890, 885733…
#>  6 <int>        0 <int [0]>  <int>      0.260   0.244 (((747008 1925789, 746630…
#>  7 <int>        5 <int [5]>  <int>      0.00147 0.003 (((818893 2514767, 818614…
#>  8 <int>        5 <int [5]>  <int>      0.00147 0.002 (((509103 1747787, 508820…
#>  9 <int>        3 <int [3]>  <int>      0.0782  0.101 (((775400 2345600, 775068…
#> 10 <int>        4 <int [4]>  <int>      0.0141  0.016 (((626230 1810121, 626269…
#> # ℹ 75 more rows