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Alias for stan_jsdm with method = "gllvm"

stan_gllvm.Rd

Alias for stan_jsdm with method = "gllvm"

Usage

stan_gllvm(X, ...)

# Default S3 method
stan_gllvm(
  X = NULL,
  Y = NULL,
  D = NULL,
  species_intercept = TRUE,
  dat_list = NULL,
  family,
  site_intercept = "none",
  prior = jsdm_prior(),
  save_data = TRUE,
  iter = 4000,
  ...
)

# S3 method for class 'formula'
stan_gllvm(formula, data = list(), ...)

Arguments

X

The covariates matrix, with rows being site and columns being covariates. Ignored in favour of data when formula approach is used to specify model.

...

Arguments passed to rstan::sampling()

Y

Matrix of species by sites. Rows are assumed to be sites, columns are assumed to be species

D

The number of latent variables within a GLLVM model

species_intercept

Whether the model should be fit with an intercept by species, by default TRUE

dat_list

Alternatively, data can be given to the model as a list containing Y, X, N, S, K, and site_intercept. See output of jsdm_sim_data() for an example of how this can be formatted.

family

is the response family, must be one of "gaussian", "neg_binomial", "poisson", "binomial", "bernoulli", or "zi_poisson". Regular expression matching is supported.

site_intercept

Whether a site intercept should be included, potential values "none" (no site intercept), "grouped" (a site intercept with hierarchical grouping) or "ungrouped" (site intercept with no grouping)

prior

Set of prior specifications from call to jsdm_prior()

save_data

If the data used to fit the model should be saved in the model object, by default TRUE.

iter

A positive integer specifying the number of iterations for each chain, default 4000.

formula

The formula of covariates that the species means are modelled from

data

Dataframe or list of covariates.

Methods (by class)

  • stan_gllvm(default): Default

  • stan_gllvm(formula): Formula interface