simulate_SDM {sjSDM}

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