Ensemble Platform for Species Distribution Modeling

Functions for species distribution modeling, calibration and evaluation, ensemble of models.


3.3-6 (2016-01-14)

  • add get_predictions function for ensemble models

3.3-5 (2016-01-04)

  • MARS models are now computed throw earth package (was mda in previous verisons)
  • MARS now supports factorial explanatory variables
  • MARS now supports formula

3.3-4 (2015-11-04)

  • update biomod tuning function (Frank B.)

3.3-3 (2015-10-27)

  • force sampling of each level of factorial variables
  • add 'betamultiplier' parameter to tune MAXENT.Phillips (Frank B. request)

3.3-00 (2015-10-05) MAJOR RELEASE

  • optimize the memory consumtion of projections and ensemble projections procedure
  • add the possibility to run MAXENT.Phillips with proper background data
  • classical version of MAXENT has been renamed MAXENT.Phillips
  • add a new version of MAXENT MAXENT.Tsuruoka

3.2-00 (2015-07-28)

  • add 3 new functions in biomod2 (Frank B. contribution)
  • BIOMOD_cv to control models cross validation procedure
  • BIOMOD_presenceonly to evaluate biomods models using boyce and mpa indices
  • BIOMOD_tuning to automatically tune BIOMOD_ModelingOptions parameters

3.1-59 (2014-10-23) * add model evaluation scores plottinfg function * dependence to ggplot2

3.1-53 (2014-08-06) * new ensemble models names to be more coherent with formal models names

3.1-44 (2014-05-20) * possibility to use user defined function to influence the way models are weighted in weighted mean ensemble models (Thanks to Frank B.)

3.1-43 (2014-05-20) * add of as.data.frame argument for get_evaluations() function to enable formal and ensemble models' evaluation scores merging

3.1-42 (2014-05-19) * enable ensemble forecasting models selection (Thanks to Robin E.)

3.1-17 (2013-10-23) * add parameter to control amount of memory reserved for MAXENT calculations (via java) (Thanks to Burke G.) * optimisation of memory consumsion in models projections when do.stack argument is set to FALSE * binary and filtering projections output re-activated

3.1-1 (2013-09-04) * limitation of package dependencies * fairely definition of package namespace * add functions to update biomod2 objects from a version to the current one

3.0.2 (2013-07-23) * new fonctions to evaluate a-posteriori models quality * remove weights for models scaling and set it FALSE by default

3.0.0 (2013-07-01) * major realeases! * ensemble models are now biomod2 models objects (should be predicted, evaluated, and you can do variables importance) the same way than all formal biomod2 models. * possibility to produce ensemble models response plot. * ensemble forecasting output is now a biomod2_preojection object: should be plotted... * ensemble forecasting is now doable without doing previous projections (even if it is still advised). Can work with raw explanatory variables. * getter and setter function have been renamed * new variable_importance function. * ...

2.1.37 (2013-06-12) * change (temporally?) gam default package from 'mgcv' to 'gam' to deal with memory (cache) over-consuming (Thanks to Burke G.) * update of response.plot2 function (optimization + deal with factorial variables)

2.1.32 (2013-05-30) * weights for user defined pseudo-absences are now supported (thanks to Rui F.) * deal with unknown factors predictions (thanks to Denis M.)

2.1.13 (2013-03-06) * Add ProbDensFunc() function to package to produce nice plots that show inter-models variability

2.1.12 (2013-03-04) * add rasterVis dependency for nicer biomod2 plots * PA.dist.min and PA.dist.max are now defined in meters when you work with unprojected rasters in disk pseudo absences selection

2.1.9 (2013-02-28) * possibility to indicate manually which data should be used for calibration (resp. for validation) of models within BIOMOD_Modeling

2.1.9 (2013-02-27) * one var modeling supported (thanks Anne O.) * new options for response curves plotting (col, lty, data_species...)

2.1.8 (2013-02-25)

  • response plot supports now formal models

2.1.0 (2013-02-21)

    • add of a modelling.id arg (BIOMOD_Modeling) for prevent from no wanted models overwriting and facilitate models tests and comparisons (thanks Frank B.)
    • change of biomod2 dataset
    • vignettes and help files update (thanks Sam P. & Signe N.)
    • save link between modeling and projection objects
    • add pROC package dependency
    • add a modeling cleaner that remove modeling objects from both memory and hard drive: RemoveProperly()

2.0.11 (2013-02-18) * possibility to consider a user.defined pseudo absences selection (thanks to Signe N.) * possibility to switch off stepwise glm selection (thanks Frank B.)

2.0.9 (2013-02-15) * automatic save on hard drive of BIOMOD_Projection outputs

2.0.8 (2013-02-14) * BIOMOD_LoadModels supports multiple models input * deal with NA in evaluation table issue (thanks Frank B.)

2.0.7 (2013-02-12) * bug on weights corrected (thanks to Lugi M.)

2.0.3 (2013-01-18) * deal with MAXENT categorical variables and categorical raster input

2.0.0 (2013-01-17)

    • models built within biomod2 are now defined as "biomod2 models objects" (own scaling models, own predict function,...)
    • full paths are replaced by relative paths to favorise portability
    • harmonization of names of objects that are saved on hard drive (more coherence between functions)
  • possibility to save projections directly in raster format (.grd or .img)

1.x.x * development phase

Reference manual

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3.3-7 by Damien Georges, 2 years ago

Report a bug at < https://r-forge.r-project.org/R/?group_id=302>

Browse source code at https://github.com/cran/biomod2

Authors: Wilfried Thuiller [aut, cre], Damien Georges [aut, cre], Robin Engler [aut], Frank Breiner [aut]

Documentation:   PDF Manual  

GPL-2 license

Imports abind, rasterVis, pROC, nnet, gbm, mda, randomForest, rpart, MASS, methods, PresenceAbsence, dismo, maxent, earth

Depends on stats, utils, sp, raster, parallel, reshape, ggplot2

Suggests ade4, foreign, Hmisc, mgcv, gam, testthat, ecospat, caret

Imported by ecospat.

Suggested by marinespeed.

See at CRAN