是的，当您在nndist()中使用参数by = "marks"时，您可以获得从每个数据点到由模式标记指定的每个物种的最近其他点的距离（无论您的点在什么维度上-在本例中为维度4）。

library(spatstat)
co <- as.data.frame(matrix(runif(10*4), ncol = 4))
dat <- cbind(co, species = rep(c("a","b"), each = 5))
dat
#>            V1         V2         V3          V4 species
#> 1  0.63445421 0.02342485 0.81973509 0.747078710       a
#> 2  0.64659444 0.08671850 0.41461989 0.479899769       a
#> 3  0.98141590 0.91534392 0.11993177 0.225535950       a
#> 4  0.08795223 0.08288239 0.50009446 0.604776775       a
#> 5  0.10289099 0.48330815 0.68406240 0.035143386       a
#> 6  0.11829745 0.19811870 0.65028245 0.482867938       b
#> 7  0.32563624 0.55886364 0.17271701 0.001583984       b
#> 8  0.28140749 0.38131846 0.09478723 0.404689925       b
#> 9  0.14586923 0.86017444 0.20450944 0.786701343       b
#> 10 0.95229731 0.94235418 0.94513459 0.605581855       b
X <- ppx(dat)
X
#> Multidimensional point pattern
#> 10 points 
#> 4-dimensional space coordinates (V1,V2,V3,V4)
#> 1 column of marks: 'species'
nndist(X, by = "marks")
#>            a         b
#> 1  0.4895471 0.6288539
#> 2  0.4895471 0.5728002
#> 3  0.9748167 0.7810672
#> 4  0.5787884 0.2271969
#> 5  0.7203404 0.5321360
#> 6  0.2271969 0.6122530
#> 7  0.5638479 0.4494952
#> 8  0.5728002 0.4494952
#> 9  0.8532317 0.6369029
#> 10 0.9093800 1.1128385