                 Changes in version 2.0.2 (2025-12-14)                  

  - Switch all the parallelization to futures. See vignette("Runtime")
  - Switch all the progress updates to progressr. Progress updates are
    now also available for parallel processing and are customizable.
  - Process are much more RAM efficient now.

                        Changes in version 2.0.1                        

  - Fix bug in SDTree and SDForest where an error occurred, if X had
    columns with only one unique value.

                 Changes in version 2.0.0 (2025-12-04)                  

  - Removal of data.tree dependence. Trees are now saved as a matrix.
  - This results in a substantial reduction of RAM usage and space
    needed to save an SDTree or SDForest. It also results in increased
    computational speed.
  - Removal of copy, fromList, and toList. Remove the copy arguments
    from all pruning involving functions.
  - New plotting of SDTree objects.
  - Improved/Robust parallelization.
  - Remove gpu support and dependence on GPUmatrix due to it being
    scheduled for archiving.

                 Changes in version 1.0.13 (2025-06-05)                 

  - In case of parallel processing use random number generator
    "L'Ecuyer-CMRG" for reproducibility

                       Changes in version 1.0.12                        

  - Fix extended SDAM example

                       Changes in version 1.0.11                        

  - Add option to plot SDForests. The plot shows the out-of-bag
    performance against the number of trees. This helps to evaluate
    whether enough trees were used.

                 Changes in version 1.0.10 (2025-05-09)                 

  - Added feature to select some predictors not to be regularized closes
    option to use some covariates not regularized in SDAM #4
  - Fix the length of the coefficient list to the number of predictors
    and name the elements
  - change predict_individual_j to expect a numeric new data vector
    instead of a whole data.frame

                        Changes in version 1.0.9                        

  - Add the option to select some variables as predictors in SDTree and
    SDForest.

                        Changes in version 1.0.8                        

  - Fix various bugs on edge cases with just one variable or just one
    tree
  - SDForest, regPath.SDTree, regPath.SDForest, predict.SDForest,
    prune.SDForest, varImp.SDTree

                 Changes in version 1.0.7 (2025-04-09)                  

  - Fix bug in estimation of SDTree when using only one covariate (did
    stop splitting after one split)
  - Add support to predict with an SDForest using multiple cores in
    parallel

                        Changes in version 1.0.6                        

  - Fix bug in SDTree.predict(), when predicting using only one
    covariate

                        Changes in version 1.0.5                        

  - Fix bug in plot of paths using plotly (remove expression Pi in case
    of plotly)

                 Changes in version 1.0.4 (2025-02-19)                  

  - Initial CRAN submission.
