Package index • biomod2

Modeling species distributions
Main functions
`BIOMOD_FormatingData()`	Format input data, and select pseudo-absences if wanted, for usage in biomod2
`BIOMOD_Modeling()`	Run a range of species distribution models
`BIOMOD_Projection()`	Project a range of calibrated species distribution models onto new environment
`BIOMOD_EnsembleModeling()`	Create and evaluate an ensemble set of models and predictions
`BIOMOD_EnsembleForecasting()`	Project ensemble species distribution models onto new environment
`BIOMOD_RangeSize()`	Analyze the range size differences between projections of species distribution models
`BIOMOD_LoadModels()`	Load species distribution models built with biomod2
Secundary functions
`bm_MakeFormula()`	Standardized formula maker
`bm_SampleBinaryVector()`	Sample binary vector
`bm_SampleFactorLevels()`	Sample all levels of a factorial variable
`bm_PseudoAbsences()` `bm_PseudoAbsences_user.defined()` `bm_PseudoAbsences_random()` `bm_PseudoAbsences_sre()` `bm_PseudoAbsences_disk()`	Select pseudo-absences
`bm_CrossValidation()` `bm_CrossValidation_user.defined()` `bm_CrossValidation_random()` `bm_CrossValidation_kfold()` `bm_CrossValidation_block()` `bm_CrossValidation_strat()` `bm_CrossValidation_env()`	Build cross-validation table
`bm_ModelingOptions()`	Configure the modeling options for each selected model
`bm_Tuning()`	Tune models parameters
`bm_RunModelsLoop()` `bm_RunModel()`	Loop to compute all single species distribution models
`bm_SRE()`	Surface Range Envelope
`bm_FindOptimStat()` `get_optim_value()` `bm_CalculateStat()`	Calculate the best score according to a given evaluation method
`bm_BinaryTransformation()`	Convert probability values into binary values using a predefined threshold
`bm_VariablesImportance()`	Variables' importance calculation
`bm_PlotEvalMean()`	Plot mean evaluation scores
`bm_PlotEvalBoxplot()`	Plot boxplot of evaluation scores
`bm_PlotVarImpBoxplot()`	Plot boxplot of variables importance
`bm_PlotResponseCurves()`	Plot response curves
`bm_PlotRangeSize()`	Plot species range change
Toolbox
Objects
`BIOMOD.formated.data(<numeric>,<data.frame>)` `BIOMOD.formated.data(<data.frame>,<ANY>)` `BIOMOD.formated.data(<numeric>,<matrix>)` `BIOMOD.formated.data(<numeric>,<SpatRaster>)` `show(<BIOMOD.formated.data>)`	`BIOMOD_FormatingData()` output object class
`BIOMOD.formated.data.PA(<numeric>,<data.frame>)` `BIOMOD.formated.data.PA(<numeric>,<SpatRaster>)`	`BIOMOD_FormatingData()` output object class (with pseudo-absences)
`plot(<BIOMOD.formated.data>,<missing>)`	`plot` method for `BIOMOD.formated.data` object class
`summary(<BIOMOD.formated.data>)`	`summary` method for `BIOMOD.formated.data` object class
`BIOMOD.options.default(<character>,<character>)`	`bm_ModelingOptions` output object class
`BIOMOD.options.dataset(<character>)` `show(<BIOMOD.options.dataset>)` `print(<BIOMOD.options.dataset>)`	`bm_ModelingOptions` output object class
`show(<BIOMOD.models.options>)` `print(<BIOMOD.models.options>)`	`bm_ModelingOptions` output object class
`BIOMOD.stored.data` `BIOMOD.stored.data-class` `BIOMOD.stored.data.frame-class` `BIOMOD.stored.SpatRaster-class` `BIOMOD.stored.files-class` `BIOMOD.stored.formated.data-class` `BIOMOD.stored.options-class` `BIOMOD.stored.models.out-class`	`BIOMOD_Modeling` and `BIOMOD_EnsembleModeling` output object class
`show(<biomod2_model>)`	Single model output object class (when running `BIOMOD_Modeling()`)
`show(<biomod2_ensemble_model>)`	Ensemble model output object class (when running `BIOMOD_EnsembleModeling()`)
`show(<BIOMOD.models.out>)`	`BIOMOD_Modeling()` output object class
`plot(<BIOMOD.projection.out>,<missing>)` `show(<BIOMOD.projection.out>)`	`BIOMOD_Projection()` output object class
`show(<BIOMOD.ensemble.models.out>)`	`BIOMOD_EnsembleModeling()` output object class
Getters
`load_stored_object()`	Functions to load `BIOMOD.stored.data` objects
`get_formal_model(<biomod2_model>)` `get_scaling_model(<biomod2_model>)`	Functions to extract informations from `biomod2_model` objects
`get_species_data(<BIOMOD.formated.data>)` `get_species_data(<BIOMOD.formated.data.PA>)` `get_eval_data(<BIOMOD.formated.data>)` `get_options(<BIOMOD.models.out>)` `get_calib_lines(<BIOMOD.models.out>)` `get_formal_data(<BIOMOD.models.out>)` `get_predictions(<BIOMOD.models.out>)` `get_built_models(<BIOMOD.models.out>)` `get_evaluations(<BIOMOD.models.out>)` `get_variables_importance(<BIOMOD.models.out>)` `get_projected_models(<BIOMOD.projection.out>)` `free(<BIOMOD.projection.out>)` `get_predictions(<BIOMOD.projection.out>)` `get_formal_data(<BIOMOD.ensemble.models.out>)` `get_built_models(<BIOMOD.ensemble.models.out>)` `get_kept_models(<BIOMOD.ensemble.models.out>)` `get_predictions(<BIOMOD.ensemble.models.out>)` `get_evaluations(<BIOMOD.ensemble.models.out>)` `get_variables_importance(<BIOMOD.ensemble.models.out>)`	Functions to extract informations from `BIOMOD.models.out`, `BIOMOD.projection.out` or `BIOMOD.ensemble.models.out` objects
`predict(<biomod2_model>)`	Functions to get predictions from `biomod2_model` objects
`predict.em`	Functions to get predictions from `biomod2_ensemble_model` objects
Data
Models options
`ModelsTable`	Single models package and functions
`OptionsBigboss`	Bigboss pre-defined parameter values for single models
Species data
`DataSpecies`	Presence-Absence data to build test SDM
Environmental data
`bioclim_current`	Bioclimatic variables for SDM based on current condition
`bioclim_future`	Bioclimatic variables for SDM based on future condition

Reference

Modeling species distributions

Main functions

Secundary functions

Toolbox

Objects

Getters

Data

Models options

Species data

Environmental data