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Set of functions to facilitate the use of caretSDM through tidyverse grammatics.
select_predictors(x, ...)# S3 method for sdm_area select(.data, ...)# S3 method for input_sdm select(.data, ...)# S3 method for sdm_area mutate(.data, ...)# S3 method for input_sdm mutate(.data, ...)# S3 method for sdm_area filter(.data, ..., .by, .preserve)# S3 method for input_sdm filter(.data, ..., .by, .preserve)# S3 method for occurrences filter(.data, ..., .by, .preserve)filter_species(x, spp = NULL, ...)
# S3 method for sdm_area select(.data, ...)
# S3 method for input_sdm select(.data, ...)
# S3 method for sdm_area mutate(.data, ...)
# S3 method for input_sdm mutate(.data, ...)
# S3 method for sdm_area filter(.data, ..., .by, .preserve)
# S3 method for input_sdm filter(.data, ..., .by, .preserve)
# S3 method for occurrences filter(.data, ..., .by, .preserve)
filter_species(x, spp = NULL, ...)
The transformed sdm_area/input_sdm object.
sdm_area
input_sdm
sdm_area or input_sdm object.
character arguments to pass to the given function.
character
Data to pass to tidyr function.
See ?dplyr::filter.
Species to be filtered.
# Create sdm_area object: sa <- sdm_area(parana, cell_size = 25000, crs = 6933) # Include predictors: sa <- add_predictors(sa, bioc) |> select_predictors(c("bio1", "bio4", "bio12"))
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