Iterate over multiple sampling methods and sample sizes

Usage

monte_carlo(
  data,
  metrics = NULL,
  nSamp,
  iter,
  method = NULL,
  cores = NULL,
  ...
)

Arguments

data: an sf of type POINT
metrics: a vector of character strings that match desired column names in data
nSamp: a numeric scalar greater than 0 and less than the number of rows in data
iter: a numeric scalar greater than 0
method: The method to use for sampling. Can be "clhs" for Latin Hypercube Sampling, "balanced" else for Balanced Sampling, "srs" for Simple Random Sampling, or "strat" for stratified sampling. If method = "strat", data must have an attribute named strata
cores: Number of cores to use for parallel computation
...: parameters to pass to sgsR::sample_ahelssample_ahels

Value

a list of sampled datasets

Details

This function iterates over multiple sampling methods and sample sizes using utils_sample(). The function assumes that users have removed coordinate columns if a data.frame has been provided. Any NA values in data will be dropped.