Changes in version 1.1.3 (2026-05-08)                  

Breaking changes (API style)

  - Per common R conventions, all exported function names now use
    lowercase (including main constructors sce() and sca()).
  - S3 class names are now "sce" and "sca" (previously "SCE" and "SCA").
    Method names follow (print.sce, predict.sca, etc.).
  - All function arguments now use lowercase / snake_case. Renamed
    arguments include:
      - Training_data -> training_data, Testing_data -> testing_data
      - X -> x, Y -> y, X_sample -> x_sample
      - Nmin -> nmin, Ntree -> ntree
      - Predictors -> predictors, Predictant -> predictant, Simulations
        -> simulations
      - OOB_weight -> oob_weight
      - Internal helpers: Max_merge_iter -> max_merge_iter, Weak_L ->
        weak_l
      - Affected functions: sce(), sca(), rfe_sce(), model_simulation(),
        sca_tree_predict(), sce_model_evaluation(),
        sca_model_evaluation(), wilks_importance(), S3 methods
        predict.*, importance.*, evaluate.*, etc.
  - Renamed functions include (non-exhaustive): model_simulation(),
    sca_tree_predict(), sce_model_evaluation(), sca_model_evaluation(),
    wilks_importance(), sca_importance(), rfe_sce(), plot_rfe(), and
    internal helpers such as sce_prediction(), training_prediction(),
    oob_validation(), gof(), nse_equation(), kge_equation(),
    inference().
  - Saved .RDS / .RData models created with older versions store the
    previous class names; assign new classes before using S3 methods,
    e.g. class(obj) <- "sce" or class(obj) <- "sca" as appropriate.

Bug fixes

  - sce(parallel = TRUE) no longer fails on single-core machines (or
    when Ntree == 1); it now falls back to sequential execution instead
    of leaving the result vector undefined. The cluster is also released
    via on.exit() so a worker error no longer leaks the cluster.

Documentation

  - Updated README.md, tutorial script, and manual pages to match the
    new function and dataset names.

                 Changes in version 1.1.2 (2025-10-04)                  

New Features

  - Added digits argument for variable importance outputs
      - Wilks_importance() and SCA_importance() now round
        Relative_Importance to digits decimal places (default: 2)
      - S3 methods importance.SCE() and importance.SCA() accept and
        forward the digits argument

Documentation

  - Updated man/importance.Rd to document the digits parameter and
    default
  - Updated README examples to demonstrate importance(..., digits = 2)

Compatibility

  - Backward compatible; only changes displayed precision of importance
    values. Adjust digits to control rounding

                 Changes in version 1.1.1 (2025-07-25)                  

New Features

  - Added parameter validation warnings to evaluate() S3 methods
      - evaluate.SCA() now automatically retrieves predictants from the
        model object (no need to specify)
      - evaluate.SCA() now specifically warns if Training_data is
        provided (not needed for SCA evaluation)
      - evaluate.SCE() now automatically retrieves predictants from the
        model object (no need to specify)
      - Both methods now warn if extra parameters beyond required ones
        are provided
  - Enhanced user experience by providing clear guidance on correct
    parameter usage

                 Changes in version 1.1.0 (2025-07-02)                  

New Features

  - Added S3 class system for SCE and SCA objects with dedicated methods
  - Implemented print(), summary(), predict(), importance(), and
    evaluate() methods for S3 objects
  - Added Plot_RFE() function for visualizing recursive feature
    elimination results
  - Enhanced backward compatibility - functions now work with both S3
    objects and legacy list formats

Improvements

  - Improved parallel processing with proper function exports to cluster
  - Enhanced error handling and input validation
  - Updated documentation with comprehensive examples using S3 methods
  - Consolidated documentation files for better organization

Bug Fixes

  - Resolved S3 method dispatch problems
  - Corrected parameter order in Model_simulation() and
    SCA_tree_predict() functions

Documentation

  - Updated all .Rd files to use S3 methods in examples
  - Added comprehensive README with installation and usage instructions
  - Improved function documentation with better examples
  - Added cross-references between related functions

Technical Changes

  - Added proper NAMESPACE configuration with S3 method registrations
  - Imported required graphics functions (legend, lines) for plotting
  - Enhanced package structure for better maintainability