embedding spatial cross sectional data

Usage

# S4 method for class 'sf'
embedded(data, target, E = 3, tau = 1, nb = NULL, trend.rm = FALSE)

# S4 method for class 'SpatRaster'
embedded(data, target, E = 3, tau = 1, trend.rm = FALSE)

Arguments

data: The observation data.
target: Name of target variable.
E: (optional) Dimensions of the embedding.
tau: (optional) Step of spatial lags.
nb: (optional) The neighbours list.
trend.rm: (optional) Whether to remove the linear trend.

Value

A matrix

Examples

columbus = sf::read_sf(system.file("case/columbus.gpkg", package="spEDM"))
embedded(columbus,target = "crime", E = 3)
#>           [,1]     [,2]     [,3]
#>  [1,] 24.71427 41.55964 43.45135
#>  [2,] 26.24684 44.57868 40.73529
#>  [3,] 29.41175 43.45135 37.55683
#>  [4,] 34.64648 37.95647 38.69064
#>  [5,] 40.46533 34.43484 42.28334
#>  [6,] 40.62371 39.75806 38.34769
#>  [7,] 49.72845 49.78631 36.31338
#>  [8,] 41.49913 38.07163 35.85632
#>  [9,] 36.94778 41.85353 35.95082
#> [10,] 25.32838 39.49545 42.28606
#> [11,] 49.85745 37.09881 38.36157
#> [12,] 43.25009 47.11232 41.51302
#> [13,] 38.09398 49.78631 36.31338
#> [14,] 42.82054 49.93589 43.02258
#> [15,] 50.10508 41.28794 33.22773
#> [16,] 52.36547 40.54196 32.41137
#> [17,] 18.09105 33.36364 40.69429
#> [18,] 51.18117 49.62083 37.60425
#> [19,] 46.44216 48.68181 44.85538
#> [20,] 32.44636 40.69429 42.26294
#> [21,] 43.72131 40.69917 42.98493
#> [22,] 35.90408 39.77205 38.67724
#> [23,] 18.74605 33.41324 42.87320
#> [24,] 54.90556 47.62725 28.68877
#> [25,] 49.97125 43.08921 27.40518
#> [26,] 48.62931 43.49389 35.84862
#> [27,] 33.20420 37.93095 38.70860
#> [28,] 47.42423 34.84094 37.55877
#> [29,] 51.79066 40.90736 34.22474
#> [30,] 48.57333 43.06283 34.01979
#> [31,] 19.12682 24.36550 53.59496
#> [32,] 13.85469 37.10639 44.54546
#> [33,] 37.27827 36.59480 37.48687
#> [34,] 22.13718 35.70533 52.96964
#> [35,] 33.09855 34.84292 47.90205
#> [36,] 18.75491 40.07407 53.59496
#> [37,] 50.99422 38.49387 34.09606
#> [38,] 43.65271 36.05057 35.77420
#> [39,] 16.17110 20.23296 40.07407
#> [40,] 21.05449 38.46893 40.90633
#> [41,] 21.06992 19.81578 40.31098
#> [42,] 19.13979 23.34567 53.59496
#> [43,] 36.16118 38.21957 34.95754
#> [44,] 35.74727 35.36815 37.17430
#> [45,] 32.07386 50.90175 36.17484
#> [46,] 16.70321 19.38104 40.07407
#> [47,] 17.57322 19.51481 38.46893
#> [48,] 28.54896 45.11036 40.83259
#> [49,] 27.21201 42.99867 40.83259