cpr_rand_comm {canaper} | R Documentation |
Note that binary null models return a binary matrix, even if an abundance matrix was used as input.
cpr_rand_comm(comm, null_model, n_iterations = 1, thin = 1, seed = NULL)
comm |
Dataframe or matrix; input community data with sites (communities) as rows and species as columns. Values of each cell are the presence/absence (0 or 1) or number of individuals (abundance) of each species in each site. |
null_model |
Character vector of length 1 or object of class |
n_iterations |
Numeric vector of length 1; number of iterations for sequential null models. Ignored by non-sequential null models. |
thin |
Numeric vector of length 1; thinning parameter used by some
null models in |
seed |
Integer vector of length 1 or NULL; random seed that will be used
in a call to |
Matrix
set.seed(12345)
# Check list of available pre-defined null models in vegan
vegan::make.commsim()
# Binary null model produces binary output
data(phylocom)
cpr_rand_comm(phylocom$comm, "swap", 100)
# Quantitative null model produces quantitative output
cpr_rand_comm(phylocom$comm, "swap_count", 100)
# How to use a custom null model
# 1. Define a randomizing function, e.g. re-sample the matrix while
# preserving total number of presences (same as the "r00" model)
randomizer <- function(x, n, ...) {
array(replicate(n, sample(x)), c(dim(x), n))
}
# 2. Generate a commsim object
cs_object <- vegan::commsim(
"r00_model",
fun = randomizer, binary = TRUE,
isSeq = FALSE, mode = "integer"
)
# 3. Generate the null community
cpr_rand_comm(phylocom$comm, cs_object, 100)