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caretSDM 1.1.0

CRAN release: 2025-07-09

  • Initial CRAN submission.

caretSDM 1.1.1

  • Inclusion of Non-native Distribution using caretSDM with adaptations on sdm_area function to allow the use of scenarios that do not particularly match the modeling area.

caretSDM 1.1.2

  • Inclusion of methods to include new algorithms in caretSDM.

caretSDM 1.1.3

  • Inclusion of Ensemble of Small Models in caretSDM.

caretSDM 1.1.4

CRAN release: 2025-08-29

  • Inclusion of functions to add different classes together, as well as plots for niche and background. First attempts to include independent test data. tSNE is also working properly now. Inclusion of testing to improve code coverage.

caretSDM 1.1.5

  • Plotting ensemble predictions is working. Added blockCV methods for crossvalidation.

caretSDM 1.2

  • Inclusion of MaxEnt and Mahalanobis Distance directly on caretSDM.
  • Pseudoabsences can now be retrieved outside a buffer.
  • Inclusion of functions: correlate_sdm, prediction_change_sdm and tuneGrid_sdm.

caretSDM 1.2.1

  • A error on plots assertion was corrected to better describe assertion problems.

caretSDM 1.2.2

  • A CRS correction for add_scenarios function was missing for the crop_area parameter.

caretSDM 1.2.3

CRAN release: 2025-11-06

  • There was a problem with add_scenarios function when adding a stars with a crop_by.

caretSDM 1.2.4

  • input_sdm now checks if user passed occurrences to join_area.

caretSDM 1.2.5

CRAN release: 2026-01-08

  • buffer_sdm function now has a convex hull argument, allowing a buffer to be created around it.
  • WorldClim_data function now uses httr2 package to gracefully handle errors.

caretSDM 1.3

  • caretSDM now does not allow to run maxent without previously run the background function.

caretSDM 1.4

  • Package assertions is now performed by checkCLI package.

caretSDM 1.5

CRAN release: 2026-03-10

  • Ensembles and projections performance were dramatically tunned to be more efficient.

caretSDM 1.6

  • Inclusion of pseudoabsence selection through a custom function.

caretSDM 1.6.1

  • Inclusion of background selection through a custom function.

caretSDM 1.7

  • predict_sdm doesn’t perform ensembles anymore.
  • Ensembles are included in the ensembles_sdm function.
  • All adjusts necessary to properly perform that operation, including tests, are implemented.
  • Vignettes and examples were changed to include ensembles_sdm function.
  • data_clean now accepts a custom function to clean occurrences.

caretSDM 1.8

  • New wrapper for multicollinearity reduction with PCA, VIF and custom functions.
  • Pseudoabsences and ensemble now accept custom functions.
  • crop_by in sdm_area now performs masking.

caretSDM 1.8.1

  • A minor adjustment to predict_sdm was necessary to allow for multiple scenarios.

caretSDM 1.8.2

  • Models IDs were changed.

caretSDM 1.8.3

CRAN release: 2026-05-12

  • Inclusion of ECDFniche to provide the mahalanobis distance method.

caretSDM 1.9

  • Some packages were moved from Imports do Suggestions and now are used conditionally along the package functions.

caretSDM 1.9.1

  • The process now accepts that models can fail.

caretSDM 1.9.2

  • ‘crs’ argument in occurrences_sdm and sdm_area is now changed to ‘occ_crs’ and ‘output_crs’, respectively.

caretSDM 1.9.3

  • New assertions to avoid errors when plotting, using MEM, ESM, PDP, validation metrics, background and scenarios.
  • Correction for MaxEnt: models were trained using background as presences.
  • Inclusion of a first draft of a stacking meta-learner modeling (stack_sdm).
  • I changed the print objects to be more similar with ODMAP protocol.

caretSDM 1.9.4

  • Mapview from ensembles and predictions were corrected.

caretSDM 1.9.5

  • Assertion on add_scenarios were missing.
  • get_ensembles now returns maps and not just the final matrix.

caretSDM 1.9.6

  • Correction on add_scenarios and sdm_area to allow the usage of a character (automatizing the import of data through these functions).
  • Use of Rmd in documentation.
  • Change in add_scenarios naming.