BIOMOD.ensemble.models.out: 'BIOMOD_EnsembleModeling()' output object class
In biomod2: Ensemble Platform for Species Distribution Modeling

BIOMOD.ensemble.models.out

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 BIOMOD.ensemble.models.out object

Slots

modeling.id: a character corresponding to the name (ID) of the simulation set
dir.name: a character corresponding to the modeling folder
sp.name: a character corresponding to the species name
expl.var.names: a vector containing names of explanatory variables
models.out: a BIOMOD.stored.models.out-class object containing informations from BIOMOD_Modeling object
em.by: a character corresponding to the way kept models have been combined to build the ensemble models, must be among PA+run, PA+algo, PA, algo, all
em.computed: a vector containing names of ensemble models
em.failed: a vector containing names of failed ensemble models
em.models_kept: a list containing single models for each ensemble model
models.evaluation: a BIOMOD.stored.data.frame-class object containing models evaluation
variables.importance: a BIOMOD.stored.data.frame-class object containing variables importance
models.prediction: a BIOMOD.stored.data.frame-class object containing models predictions
models.prediction.eval: a BIOMOD.stored.data.frame-class object containing models predictions for evaluation data
link: a character containing the file name of the saved object

Author(s)

Damien Georges

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)

  # Create default modeling options
  myBiomodOptions <- BIOMOD_ModelingOptions()

  # Model single models
  myBiomodModelOut <- BIOMOD_Modeling(bm.format = myBiomodData,
                                      modeling.id = 'AllModels',
                                      models = c('RF', 'GLM'),
                                      bm.options = myBiomodOptions,
                                      CV.strategy = 'random',
                                      CV.nb.rep = 2,
                                      CV.perc = 0.8,
                                      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

biomod2 documentation built on July 9, 2023, 6:05 p.m.