sdmWorkflow {intSDM} | R Documentation |
sdmWorkflow
: Function to compile the reproducible workflow.
Description
This function is used to compile the reproducible workflow from the R6
object created with startFunction
. Depending on what was specified before, this function will estimate the integrated species distribution model, perform cross-validation, create predictions from the model and plot these predictions.
Usage
sdmWorkflow(
Workflow = NULL,
predictionDim = c(150, 150),
predictionData = NULL,
initialValues = FALSE,
inlaOptions = list(),
ipointsOptions = NULL
)
Arguments
Workflow |
The |
predictionDim |
The pixel dimensions for the prediction maps. Defaults to |
predictionData |
Optional argument for the user to specify their own data to predict on. Must be a |
initialValues |
Find initial values using a GLM before the model is estimated. Defaults to |
inlaOptions |
Options to specify in inla from the |
ipointsOptions |
Options to specify in fm_int's |
Value
The return of the function depends on the argument Save
from the startWorkflow
function. If this argument is FALSE
then the objects will be saved to the specidfied directory. If this argument is TRUE
then a list of different outcomes from the workflow will be returned.
Examples
## Not run:
if (requireNamespace('INLA')) {
workflow <- startWorkflow(Species = 'Fraxinus excelsior',
Projection = '+proj=longlat +ellps=WGS84',
Save = FALSE,
saveOptions = list(projectName = 'example'))
workflow$addArea(countryName = 'Sweden')
workflow$addGBIF(datasetName = 'exampleGBIF',
datasetType = 'PA',
limit = 10000,
coordinateUncertaintyInMeters = '0,50')
workflow$addMesh(cutoff = 20000,
max.edge=c(60000, 80000),
offset= 100000)
workflow$workflowOutput('Model')
Model <- sdmWorkflow(workflow)
}
## End(Not run)