Changes in version 2.0.1                        

Major changes

  - train_iblm_xgb() methodology changed. The booster model component is
    now trained differently, using glm predictions as an offset for
    xgb.train() instead of the ratios method employed in versions
    ≤ 1.0.3.
  - Structure of data object freMTPLmini changed. Output of
    load_freMTPL2freq() also changed accordingly.

New features

  - The IBLM model may now be trained using a weighting variable and/or
    an offset variable. More information is available at
    https://ifoa-adswp.github.io/IBLM/articles/IBLM.html#offsetting-and-weighting.

                 Changes in version 1.0.2 (2025-12-16)                  

Major changes

  - iblm class model objects now require factor variables for
    categorical features. Users should explicitly convert character
    columns to factors before training.

New features

  - Added "IBLM" vignette providing a comprehensive walkthrough of
    package functionality.

Bug fixes

  - Fixed bug where all variable types were converted to numeric before
    training and predicting of booster model, which could lead to
    improper handling of categorical features.

Internal changes

  - Updated to maintain compatibility with xgboost v3.1.2.1. Package now
    requires xgboost >= 3.1.2.1.

                        Changes in version 1.0.0                        

  - Initial CRAN submission.