spatial pattern correlation

Usage

spc(
  data,
  overlay = "and",
  discnum = 3:8,
  discmethod = c("sd", "equal", "geometric", "quantile", "natural"),
  cores = 1
)

Arguments

data: A data.frame, tibble or sf object of observation data.
overlay: (optional) Spatial overlay method. One of and, or, intersection. Default is and.
discnum: (optional) A vector of number of classes for discretization. Default is 3:8.
discmethod: (optional) A vector of methods for discretization, default is using c("sd","equal","geometric","quantile","natural") by invoking sdsfun.
cores: (optional) Positive integer (default is 1). When cores are greater than 1, use parallel computing.

Value

A list.

cor_tbl: A tibble with power of spatial pattern correlation
cor_mat: A matrix with power of spatial pattern correlation

Examples

sim1 = sf::st_as_sf(gdverse::sim,coords = c('lo','la'))
sim1
#> Simple feature collection with 80 features and 4 fields
#> Geometry type: POINT
#> Dimension:     XY
#> Bounding box:  xmin: 1 ymin: 1 xmax: 10 ymax: 8
#> CRS:           NA
#> # A tibble: 80 × 5
#>        y    xa    xb    xc geometry
#>    <dbl> <dbl> <dbl> <dbl>  <POINT>
#>  1  0.23  1.96  4.17  4.82    (1 1)
#>  2  0.34 10.7   3.83  7.41    (2 1)
#>  3  0.32  3.08  4.23  5.25    (3 1)
#>  4  0.25  2.67  3.02  3.91    (4 1)
#>  5  0.49  9.05  3.65  6.67    (5 1)
#>  6  0.7   4.93  4.16  5.80    (6 1)
#>  7  0.8   9.99  3.86  7.19    (7 1)
#>  8  0.84  2.60  2.56  3.43    (8 1)
#>  9  0.78  8.23  2.99  5.74    (9 1)
#> 10  0.65 14.8   2.03  6.97   (10 1)
#> # ℹ 70 more rows
# \donttest{
g = spc(sim1, discnum = 3:6, cores = 1)
g
#> ***   Spatial Pattern Correlation    
#> 
#> | xv | yv | correlation |
#> |:--:|:--:|:-----------:|
#> | xc | y  |   0.11456   |
#> | xb | y  |   0.08727   |
#> | xa | y  |   0.02027   |
#> | xc | xa |   0.32194   |
#> | y  | xa |   0.03498   |
#> | xb | xa |   0.02510   |
#> | xc | xb |   0.14924   |
#> | y  | xb |   0.04607   |
#> | xa | xb |   0.04362   |
#> | xa | xc |   0.12067   |
#> | xb | xc |   0.05717   |
#> | y  | xc |   0.02997   |
plot(g,"matrix")

# }