Given the coordinates, the species' name and the environmental variables, the function creates an SWD object (sample with data).

prepareSWD(species, env, p = NULL, a = NULL, categorical = NULL)

Arguments

species

character. The name of the species.

env

stack containing the environmental variables used to extract the values at coordinate locations.

p

data.frame. The coordinates of the presence locations.

a

data.frame. The coordinates of the absence/background locations.

categorical

vector indicating which of the environmental variable are categorical, default is NULL.

Value

An SWD object.

Details

The SWD object is created in a way that the presence locations are always before than the absence/background locations.

Author

Sergio Vignali

Examples

# Acquire environmental variables files <- list.files(path = file.path(system.file(package = "dismo"), "ex"), pattern = "grd", full.names = TRUE) predictors <- raster::stack(files) # Prepare presence and background locations p_coords <- virtualSp$presence bg_coords <- virtualSp$background # Create the SWD object data <- prepareSWD(species = "Virtual species", p = p_coords, a = bg_coords, env = predictors, categorical = "biome")
#> Extracting predictor information for presence locations...
#> Extracting predictor information for absence/background locations...
data
#> Object of class SWD #> #> Species: Virtual species #> Presence locations: 400 #> Absence locations: 5000 #> #> Variables: #> --------- #> Continuous: bio1 bio12 bio16 bio17 bio5 bio6 bio7 bio8 #> Categorical: biome