Changes in version 1.1.0 - new features: - knndm for train-test splits - ffs allows for searching the whole range of predictors (earlyStopping=FALSE) - bug fix: - sampling of prediction points in geodist no longer requires reprojection and transformation of raster modeldomains by default (issue #130) - now allows for tibble in AOA - modifications: - geodist was re-structured, and some parameters have been re-named ('cvtrain' to 'CVtrain', 'cvfolds' to 'CVtest', 'type' to 'dist_space', 'timevar' to 'time_var') or newly introduced ('dist_fun', 'scale_vars') - knndm was re-structured to a lesser extent, the 'space' parameter has been re-named to 'dist_space', 'useMD' was dropped and replaced by 'dist_fun', 'scale_vars' was newly introduced - AOA as a generic - other improvements: - several new tests - added code coverage - improved documentation - unify plotting style - removed dependencies - workflow figure improved Changes in version 1.0.4 (2026-01-26) - bug fix: formatting issues in tests - references updated Changes in version 1.0.3 (2025-01-09) - bug fix: default algorithm for FNN functions changed Changes in version 1.0.2 (2024-06-14) - bug fix: tests run conditionally Changes in version 1.0.1 (2024-04-25) - bug fix: fix failed tests in global_validation Changes in version 1.0.0 (2024-04-08) - new features: - calculate local point density within AOA - option of spatial error profiles (errorProfiles with variable="geodist") - normalize_DI for a more intuitive interpretation - geodist allows calculating temporal distances - ffs now can be run in parallel (Linux only) - vignette "Cross-validation methods in CAST" - knndm in feature space (experimental) - nndm in feature space (experimental) - modifications: - function DItoErrormetric renamed to errorProfiles and allows for other dissimilarity measures - Improvement and homogenization of plotting methods for nndm, knndm and geodist objects - aoa and trainDI weight now allows list input - vignette on Introduction to CAST updated - deprecated: *plot_geodist (replaced by plot.geodist) *plot_ffs (replaced by plot.ffs) *calibrate_aoa (replaced by errorProfiles) Changes in version 0.9.0 (2024-01-09) - new features: - CAST functions now return classes with generic plotting and printing - new dataset for examples, tutorials and testing: data(splotdata) - modifications: - calibrate_aoa is now DItoErrormetric and returns a model (see function documentation) - plot_geodist is now geodist. The result can be visualized with plot() - plot_ffs is now plot(ffs) - bug fix: - fix issue #65 (threshold) - deprecated (soon): - plot_geodist, plot_ffs, calibrate_aoa Changes in version 0.8.1 (2023-05-30) - bugfix: - failed checks on Fedora 34 fixed Changes in version 0.8.0 (2023-05-21) - new features: - knndm as an alternative to nndm for large training data - modifications: - transition from raster to terra Changes in version 0.7.1 (2023-02-04) - new features: - Mahalanobis distance for AOA assessment as option - modifications: - faster estimation of the AOA - parallel option for AOA deprecated (see vignette) - delineation of the default threshold fixed as suggested in github.com/HannaMeyer/CAST/issues/46 - bugfix: - fixed issue github.com/ropensci/rnaturalearth/issues/69 Changes in version 0.7.0 (2022-08-24) - new feature: - nndm cross-validation as suggested by Milà et al. (2022) - modifications - plot_geodist works with NNDM - trainDI works with NNDM - rename of parameter folds in AOA and trainDI Changes in version 0.6.0 (2022-03-17) - new feature: - trainDI allows to calculate the DI of the training dataset separately from the aoa function - plot and print functions for the AOA - function to plot nearest neighbor distance distributions in geographic and feature space - function global_validation added - modifications - extensive restructuring of the AOA function - ffs and bss can be used with global_validation - bugfix: - error in manual assignment of weights fixed Changes in version 0.5.1 (2021-04-07) - resolved dependence on package "GSIF" which was removed from the CRAN repository Changes in version 0.5.0 (2021-02-19) - new feature: - AOA can run in parallel - calibration of the DI (calibrate_aoa) - bugfix: - aoa will work now with large training sets - modifications: - default threshold of AOA changed Changes in version 0.4.2 (2020-07-17) - new feature: - aoa now working with categorical variables - bugfix: - fixed error in ffs when >170 variables are used - minor changes: - changed order of parameters in aoa - tutorial "Introduction to CAST" improved Changes in version 0.4.1 (2020-05-19) - new feature: - vignette: tutorial introducing the "area of applicability" - variable threshold for aoa - various modifications in aoa in line with submitted paper Changes in version 0.4.0 (2020-04-06) - new feature: - new function "aoa": quantify and visualize the area of applicability of spatial prediction models - "minVar" in ffs: Instead of always starting with 2-pair combinations, ffs can now also be started with combinations of more variables (e.g starting with all combinations of 3) - bugfix: - ffs failed for "svmLinear" in previous version because of S4 class issues. Fixed now. Changes in version 0.3.1 (2018-11-19) - bugfix: - CreateSpaceTimeFolds accepts tibbles - CreateSpaceTimeFolds automatically reduces k if necessary - ffs accepts further arguments taken by caret::train - new feature: plot_ffs has option to plot selected variables only Changes in version 0.3.0 (2018-10-11) - new feature: Best subset selection (bss) with target-oriented validation as (very slow but very reliable) alternative to ffs - minor adaptations: verbose option included, improved examples for ffs - bugfix: minor adaptations done for usage with plsr Changes in version 0.2.1 (2018-07-12) - new feature: Introduction to CAST is included as a vignette. - bugfix: minor error fixed in using user defined metrics for model selection. Changes in version 0.2.0 (2018-05-03) - bugfix: ffs with option withinSE=TRUE did not choose a model as "best model" if it was within the SE of a model that was trained in an earlier run but had the same number of variables. This bug is fixed and if withinSE=TRUE ffs now only compares the performance to models that use less variables (e.g. if a model using 5 variables is better than a model using 4 variables but still in the SE of the 4-variable model, then the 4-variable model is rated as the better model). - new feature: plot_ffs plots the results of ffs to visualize how the performance changes according to model run and the number of variables being used. Changes in version 0.1.0 (2018-01-09) Initial public version on CRAN