startSpecies {PointedSDMs} | R Documentation |
startSpecies: Function used to initialize a multi-species integrated species distribution model.
Description
This function is used to create an object containing all the data, metadata and relevant components required for the multi-species integrated species distribution model and INLA to work.
As a result, the arguments associated with this function are predominantly related to describing variable names within the datasets that are relevant, and arguments related to what terms should be included in the formula for the integrated model. The output of this function is an R6
object, and so there are a variety of public methods within the output of this function which can be used to further specify the model (see ?specifySpecies
or .$help()
for a comprehensive description of these public methods).
Usage
startSpecies(
...,
spatialCovariates = NULL,
Projection,
Mesh,
speciesSpatial = "replicate",
speciesIntercept = TRUE,
speciesEnvironment = TRUE,
speciesName,
IPS = NULL,
Boundary = NULL,
pointCovariates = NULL,
Offset = NULL,
pointsIntercept = TRUE,
pointsSpatial = "copy",
responseCounts = "counts",
responsePA = "present",
trialsPA = NULL,
temporalName = NULL,
Formulas = list(covariateFormula = NULL, biasFormula = NULL)
)
Arguments
... |
The datasets to be used in the model. Must come as either |
spatialCovariates |
The spatial covariates used in the model. These covariates must be measured at every location (pixel) in the study area, and must be a |
Projection |
The coordinate reference system used by both the spatial points and spatial covariates. Must be of class |
Mesh |
An |
speciesSpatial |
Argument to specify if each species should have their own spatial effect with different hyperparameters to be estimated using INLA's "replicate" feature, of if a the field's should be estimated per species copied across datasets using INLA's "copy" feature. Possible values include: |
speciesIntercept |
Argument to control the species intercept term. Defaults to |
speciesEnvironment |
Argument to control the species environmental term. Defaults to |
speciesName |
Name of the species variable name (class |
IPS |
The integration points to be used in the model (that is, the points on the map where the intensity of the model is calculated). See |
Boundary |
A |
pointCovariates |
The non-spatial covariates to be included in the integrated model (for example, in the field of ecology the distance to the nearest road or time spent sampling could be considered). These covariates must be included in the same data object as the points. |
Offset |
Name of the offset variable (class |
pointsIntercept |
Logical argument: should the points be modeled with intercepts. Defaults to |
pointsSpatial |
Argument to determine whether the spatial field is shared between the datasets, or if each dataset has its own unique spatial field. The datasets may share a spatial field with INLA's "copy" feature if the argument is set to |
responseCounts |
Name of the response variable in the counts/abundance datasets. This variable name needs to be standardized across all counts datasets used in the integrated model. Defaults to |
responsePA |
Name of the response variable (class |
trialsPA |
Name of the trials response variable (class |
temporalName |
Name of the temporal variable (class |
Formulas |
A named list with two objects. The first one, |
Value
A specifySpecies
object (class R6
). Use ?specifySpecies
to get a comprehensive description of the slot functions associated with this object.
Note
The idea with this function is to describe the full model: that is, all the covariates and spatial effects will appear in all the formulas for the datasets and species.
If some of these terms should not be included in certain observation models in the integrated model, they can be thinned out using the .$updateFormula
function.
Note: the point covariate will only be included in the formulas for where they are present in a given dataset, and so these terms do not need to be thinned out if they are not required by certain observation models.
Examples
## Not run:
if (requireNamespace('INLA')) {
##REDO WITH OTHER DATA
#Get Data
data("SolitaryTinamou")
proj <- "+proj=longlat +ellps=WGS84"
data <- SolitaryTinamou$datasets
mesh <- SolitaryTinamou$mesh
mesh$crs <- proj
#Set base model up
baseModel <- startSpecies(data, Mesh = mesh,
Projection = proj, responsePA = 'Present',
speciesName = 'speciesName')
#Print summary
baseModel
#Set up model with dataset specific spatial fields
indSpat <- startSpecies(data, Mesh = mesh,
Projection = proj, pointsSpatial = 'individual',
responsePA = 'Present', speciesName = 'speciesName')
#Model with offset variable
offSet <- startSpecies(data, Mesh = mesh,
Projection = proj,
Offset = 'area',
responsePA = 'Present',
speciesName = 'speciesName')
#Non-random effects for the species
speciesInt <- startSpecies(data, Mesh = mesh,
Projection = proj,
speciesIntercept = FALSE,
responsePA = 'Present',
speciesName = 'speciesName')
#Turn off species level field
speciesInt <- startSpecies(data, Mesh = mesh,
Projection = proj,
speciesSpatial = NULL,
responsePA = 'Present',
speciesName = 'speciesName')
}
## End(Not run)