fit_jsdm_model()

fit_jsdm_model

R Documentation

Fit an sjSDM Model

Description

Fits a joint Species Distribution Model (jSDM) using the sjSDM package with specified abiotic, spatial, and error family configurations.

Usage

fit_jsdm_model(
  data_to_fit = NULL,
  sel_abiotic_formula = NULL,
  abiotic_method = c("linear", "DNN"),
  sel_spatial_formula = as.formula(~0 + coord_long:coord_lat),
  spatial_method = c("linear", "DNN", "none"),
  error_family = c("gaussian", "binomial"),
  device = c("cpu", "gpu"),
  parallel = 0L,
  compute_se = FALSE,
  ...,
  verbose = FALSE
)

Arguments

data_to_fit

A list containing the data to fit the model. Must include: - ‘data_community_to_fit’: matrix of community composition (constant-presence taxa already removed by ‘filter_constant_taxa()’) - ‘data_abiotic_to_fit’: data frame of abiotic variables, already scaled by ‘scale_abiotic_for_fit()’ - ‘data_coords_to_fit’: data frame of spatial coordinates

sel_abiotic_formula

A formula object specifying the abiotic (environmental) predictors

abiotic_method

Method for modeling abiotic effects. One of "linear" (default) or "DNN" (deep neural network)

sel_spatial_formula

A formula object specifying the spatial predictors. Defaults to an interaction between longitude and latitude (‘~ 0 + coord_long:coord_lat’). Only used if ‘spatial_method’ is ‘"linear"’ or ‘"DNN"’.

spatial_method

Method for modeling spatial effects. One of ‘"linear"’ (default), ‘"DNN"’ (deep neural network), or ‘"none"’ (no spatial structure)

error_family

Error family distribution. One of "gaussian" (default) or "binomial". If "binomial", community data is converted to presence/absence and a probit link is used

device

Computing device to use. One of "cpu" (default) or "gpu"

parallel

Number of CPU cores to use for parallel processing. Only applicable if device = "cpu". Default is 0L (no parallelization).

compute_se

Logical indicating whether to compute standard errors. Default is FALSE. Note: SE computation may fail with certain model configurations (e.g., DNN, complex spatial structures) and will produce a warning if it fails.

…

Additional arguments passed to sjSDM::sjSDM

Details

This function prepares the data and fits a joint Species Distribution Model using the sjSDM package. The spatial structure is modeled using an interaction term between longitude and latitude coordinates. When binomial error family is specified, the community data is converted to binary presence/absence data.

Standard error computation (‘compute_se = TRUE’) may fail with certain model configurations, particularly when using DNN methods or complex spatial structures. If SE computation fails, the model will still be returned with a warning.

Value

An object of class sjSDM containing the fitted model