simulate_SDM {sjSDM} | R Documentation |
Simulate joint Species Distribution Models
Description
Simulate species distributions
Usage
simulate_SDM(
env = 5L,
sites = 100L,
species = 5L,
correlation = TRUE,
weight_range = c(-1, 1),
link = "probit",
response = "pa",
sparse = NULL,
tolerance = 0.05,
iter = 20L,
seed = NULL
)
Arguments
env |
number of environment variables |
sites |
number of sites |
species |
number of species |
correlation |
correlated species TRUE or FALSE, can be also a function or a matrix |
weight_range |
sample true weights from uniform range, default -1,1 |
link |
probit, logit or identical |
response |
pa (presence-absence) or count |
sparse |
sparse rate |
tolerance |
tolerance for sparsity check |
iter |
tries until sparse rate is achieved |
seed |
random seed. Default = 42 |
Details
Probit is not possible for abundance response (response = 'count')
Value
List of simulation results:
env |
Number of environmental covariates |
species |
Number of species |
sites |
Number of sites |
link |
Which link |
response_type |
Which response type |
response |
Species occurrence matrix |
correlation |
Species covariance matrix |
species_weights |
Species-environment coefficients |
env_weights |
Environmental covariates |
corr_acc |
Method to calculate sign accurracy |
Author(s)
Maximilian Pichler
[Package sjSDM version 1.0.5 Index]