BIOMOD.ensemble.models.out {biomod2} | R Documentation |
BIOMOD_EnsembleModeling()
output object class
Description
Class returned by BIOMOD_EnsembleModeling
, and used by
BIOMOD_LoadModels
, BIOMOD_PresenceOnly
and
BIOMOD_EnsembleForecasting
Usage
## S4 method for signature 'BIOMOD.ensemble.models.out'
show(object)
Arguments
object |
a |
Slots
modeling.id
a
character
corresponding to the name (ID) of the simulation setdir.name
a
character
corresponding to the modeling foldersp.name
a
character
corresponding to the species nameexpl.var.names
a
vector
containing names of explanatory variablesmodels.out
a
BIOMOD.stored.models.out-class
object containing informations fromBIOMOD_Modeling
objectem.by
a
character
corresponding to the way kept models have been combined to build the ensemble models, must be amongPA+run
,PA+algo
,PA
,algo
,all
em.computed
a
vector
containing names of ensemble modelsem.failed
a
vector
containing names of failed ensemble modelsem.models_kept
a
list
containing single models for each ensemble modelmodels.evaluation
a
BIOMOD.stored.data.frame-class
object containing models evaluationvariables.importance
a
BIOMOD.stored.data.frame-class
object containing variables importancemodels.prediction
a
BIOMOD.stored.data.frame-class
object containing models predictionsmodels.prediction.eval
a
BIOMOD.stored.data.frame-class
object containing models predictions for evaluation datalink
a
character
containing the file name of the saved object
Author(s)
Damien Georges
See Also
BIOMOD_EnsembleModeling
, BIOMOD_LoadModels
,
BIOMOD_PresenceOnly
, bm_VariablesImportance
,
bm_PlotEvalMean
, bm_PlotEvalBoxplot
,
bm_PlotVarImpBoxplot
, bm_PlotResponseCurves
Other Toolbox objects:
BIOMOD.formated.data
,
BIOMOD.formated.data.PA
,
BIOMOD.models.options
,
BIOMOD.models.out
,
BIOMOD.options.dataset
,
BIOMOD.options.default
,
BIOMOD.projection.out
,
BIOMOD.stored.data
,
biomod2_ensemble_model
,
biomod2_model
Examples
showClass("BIOMOD.ensemble.models.out")
## ----------------------------------------------------------------------- #
library(terra)
# Load species occurrences (6 species available)
data(DataSpecies)
head(DataSpecies)
# Select the name of the studied species
myRespName <- 'GuloGulo'
# Get corresponding presence/absence data
myResp <- as.numeric(DataSpecies[, myRespName])
# Get corresponding XY coordinates
myRespXY <- DataSpecies[, c('X_WGS84', 'Y_WGS84')]
# Load environmental variables extracted from BIOCLIM (bio_3, bio_4, bio_7, bio_11 & bio_12)
data(bioclim_current)
myExpl <- terra::rast(bioclim_current)
## ----------------------------------------------------------------------- #
file.out <- paste0(myRespName, "/", myRespName, ".AllModels.models.out")
if (file.exists(file.out)) {
myBiomodModelOut <- get(load(file.out))
} else {
# Format Data with true absences
myBiomodData <- BIOMOD_FormatingData(resp.var = myResp,
expl.var = myExpl,
resp.xy = myRespXY,
resp.name = myRespName)
# Model single models
myBiomodModelOut <- BIOMOD_Modeling(bm.format = myBiomodData,
modeling.id = 'AllModels',
models = c('RF', 'GLM'),
CV.strategy = 'random',
CV.nb.rep = 2,
CV.perc = 0.8,
OPT.strategy = 'bigboss',
metric.eval = c('TSS','ROC'),
var.import = 3,
seed.val = 42)
}
## ----------------------------------------------------------------------- #
# Model ensemble models
myBiomodEM <- BIOMOD_EnsembleModeling(bm.mod = myBiomodModelOut,
models.chosen = 'all',
em.by = 'all',
em.algo = c('EMmean', 'EMca'),
metric.select = c('TSS'),
metric.select.thresh = c(0.7),
metric.eval = c('TSS', 'ROC'),
var.import = 3,
seed.val = 42)
myBiomodEM