as.eicm: Define a parameterized EICM model

Description

Constructs a EICM model object from given coefficients and data. Useful for simulating "true" models, otherwise only used internally.

Usage

as.eicm(
  env.coefs,
  sp.coefs = NULL,
  latent = NULL,
  options = NULL,
  occurrences = NULL,
  env = NULL,
  traits = NULL,
  intercept = TRUE,
  regularization = NULL
)

Value

A eicm object that can be used for prediction.

Arguments

env.coefs: the environmental coefficient matrix: a species x variable matrix (including intercept).
sp.coefs: the species interaction coefficient matrix: a species x species matrix, with zero diagonal.
latent: the values for the latent variables in each sample: a sample x latent variable matrix.
options: a eicm.options object defining options for fitting. Usually not needed, use forbidden, mask.sp and exclude.prevalence instead.
occurrences: a binary (0/1) sample x species matrix, possibly including NAs.
env: an optional sample x environmental variable matrix, for the known environmental predictors.
traits: an optional species x trait matrix. Currently, it is only used for excluding species interactions a priori.
intercept: logical specifying whether to add a column for the species-level intercepts.
regularization: a two-element numeric vector defining the regularization lambdas used for environmental coefficients and for species interactions respectively. See details.

Details

regularization is only used for storing the regularization lambdas used in model fitting. It is ignored in simulation.

Examples

Run this code

# Generate some coefficients
nenv <- 2
nsp <- 20
nsamples <- 200

env <- matrix(rnorm(nenv * nsamples), ncol=nenv, nrow=nsamples)
env.coefs <- matrix(runif((nenv + 1) * nsp, -4, 4), nrow=nsp)
sp.coefs <- matrix(0, nrow=nsp, ncol=nsp)
sp.coefs[3, 5] <- 3
sp.coefs[4, 8] <- 2

# Define a true model (including environmental data)
truemodel <- as.eicm(env=env, env.coefs=env.coefs, sp.coefs=sp.coefs)

# We can now realize it
predict(truemodel)