sample_existing_balanced: Sample Existing Data Using Balanced Sampling

In tgoodbody/sgsR: Structurally Guided Sampling

Sample Existing Data Using Balanced Sampling

Description

This function samples a given set of existing data using balanced sampling techniques, which ensures that each stratum or subgroup of data is proportionally represented in the sample.

Usage

sample_existing_balanced(
  existing,
  nSamp,
  algorithm = "lpm2_kdtree",
  p = NULL,
  filename = NULL,
  overwrite = FALSE,
  ...
)

Arguments

existing	sf 'POINT'. Existing plot network.
nSamp	Numeric. Number of desired samples.
algorithm	Character. One of lpm2_kdtree, lcube, lcubestratified.
p	Numeric. Vector with length equal to the number of cells in mraster representing the inclusion probability for each candidate sample. Default = nSamp / N, where N is the number of cells.
filename	Character. Path to write stratified raster to disc.
overwrite	Logical. Specify whether filename should be overwritten on disc.
...	Additional arguments to pass to the selected sampling algorithm. This is leveraged when used by sample_existing() internally

Value

An sf object that is a sub-sample of existing

tgoodbody/sgsR documentation built on March 7, 2024, 2:20 a.m.