sample_existing_clhs: Sub-sample using the conditional Latin hypercube sampling...

In tgoodbody/sgsR: Structurally Guided Sampling

Sub-sample using the conditional Latin hypercube sampling (CLHS)

Description

This function takes an existing sf object and returns a random sub-sample of size nSamp.

Usage

sample_existing_clhs(
  existing,
  nSamp,
  raster = NULL,
  cost = NULL,
  iter = 10000,
  details = FALSE,
  filename = NULL,
  overwrite = FALSE,
  ...
)

Arguments

existing	sf 'POINT'. Existing plot network.
nSamp	Numeric. Number of desired samples.
cost	Numeric/Character. Index or name of covariate within mraster to be used to constrain cLHS sampling. If default (NULL), a cost constraint is not used.
iter	Numeric. Value giving the number of iterations within the Metropolis-Hastings process.
details	Logical. If FALSE (default) output is only stratification raster. If TRUE return a list where $details is additional stratification information and $raster is the output stratification spatRaster.
filename	Character. Path to write output samples.
overwrite	Logical. Choice to overwrite existing filename if it exists.
...	Additional arguments for clhs sampling. See clhs.

Value

A subsampled SpatialPointsDataFrame object.

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