sample_background: Create sample of background points.
In juoe/sdmflow: Flexible Workflows for Species Distribution Modeling

Create sample of background points.

sample_background(x, method = "mcp", ...)

sample_background_bb(x, n = nrow(x), occ_col = "occ")

sample_background_mcp(x, n_frac = 1, n_abs = NULL, percentile = 100,
  ind_col = NULL, occ_col = "occ")

sample_background_target(x, y, n_frac = 1, n_abs = NULL,
  ind_col = NULL, occ_col = "occ")

`x`	An sf object containing the modeling data.
`method`	"mcp" or "bb"
`...`	Arguments passed on to the sample functions.
`n`	Number of background points created.
`occ_col`	Name of the occurence (presence / absence) column. Will be created if not available yet.
`n_frac`	Fraction of background samples compared to presence samples.
`n_abs`	Absolute number of background samples. Instead used of n_frac if this argument is not NULL.
`percentile`	Percentile number used for the creation of the minimum convex polygon (MCP) in which background points are sampled.
`ind_col`	Default is NULL. Can be used to specify column name identifying groups / clusters in the presence observations (e.g. individuals). Then, MCPs are calculated on a cluster-level and background points are sampled separately for each cluster.

An sf object with an additional n / nrow(x)*n_frac rows containing the background points. The feature values for the background samples will be sampled randomly from the presence samples.

juoe/sdmflow documentation built on Feb. 23, 2020, 7:38 p.m.