Generate a batch of null matrices using quantize()

Runs the stratified null model implemented in quantize() repeatedly, generating a batch of randomized matrices or, optionally, a batch of summary statistics computed from those matrices.

Usage

quantize_batch(x, n_reps = 999L, stat = NULL, n_cores = 1L, seed = NULL, ...)

Arguments

x

Community matrix (species × sites, or any numeric matrix).

n_reps

Number of randomizations to generate. Default is 999.

stat

Optional summary function taking a matrix and returning a numeric statistic (e.g. rowSums with abundance data would give total abundance per site). If NULL (default), the function returns the full set of randomized matrices.

n_cores

Number of compute cores to use for parallel processing. Default is 1.

seed

Integer used to seed random number generator, for reproducibility.

...

Additional arguments passed to quantize(), (e.g. method, breaks, n_strata, transform, offset, zero_stratum, fixed, n_iter, etc.).

Value

If stat is NULL, returns a 3D array (rows × cols × n_reps). If stat is not NULL, returns a numeric array of statistic values (dimensionality depends on stat).

Examples

set.seed(123)
x <- matrix(runif(100), nrow = 10)

# Generate 99 randomized matrices
nulls <- quantize_batch(x, n_reps = 99, method = "curvecat", n_iter = 100)

# Or compute a statistic on each
row_sums <- nullcat_batch(x, n_reps = 99, stat = rowSums,
                          method = "curvecat", n_iter = 100)

# Specify multiple cores for parallel processing
nulls <- quantize_batch(x, n_reps = 99, n_iter = 100, n_cores = 2)