Changes in version 1.0.1 (2026-03-13)                  

  - Marked the package as deprecated and directed users to rMIDAS2
  - Added a migration vignette and startup/package documentation notices
    to support existing users
  - Limited test-time thread usage to avoid CRAN check CPU-time
    inflation on Debian

                 Changes in version 1.0.0 (2023-10-11)                  

  - To mark the publication of our article in the Journal of Statistical
    Software (see citation("rMIDAS")), we are releasing our first stable
    release!
  - Minor documentation changes to reflect this publication

v0.5.0

  - rMIDAS now includes an automatic setup that prompts the user on
    whether to automatically set up a Python environment and its
    dependencies
  - Addressed dependency issues and deprecation warnings (rather a
    Python update than R)
  - An additional .Rmd example that showcases rMIDAS core functions
  - Added a new vignette for running rMIDAS in headless mode, along with
    updates to the existing vignettes
  - Updated the accompanying YAML environment file that works on all
    major operating systems (including macOS running Apple silicon
    hardware)
  - Expanded our GitHub Actions workflow to also perform R-CMD-checks on
    macOS and Windows systems
  - Updated README file

v0.4.2

  - Added headless functionality to matplotlib calls in Python
  - Updated conda setup file
  - Minor updates to underlying Python code to address deprecation
    issues

v0.4.1

  - Disabled Tensorflow deprecation warnings as default (as Python
    rather than R warning)
  - Updated accompanying YAML for easier Conda setup
  - Added no-binary pip install to YAML to resolve BLAS issues on Macs

v0.4

  - python argument in set_python_env renamed to x for clarity
  - Minor fixes including remedying bug in complete() function
  - Improved documentation

                         Changes in version 0.3                         

  - Minor updates to underlying Python code to mirror MIDASpy v1.2.1
  - Added NULL defaults to cat_cols and bin_cols parameters within
    rMIDAS::convert()
  - Overimputation legend now plotted in bottom-right corner of figure
  - Minor changes to README

                         Changes in version 0.2                         

  - rMIDAS now fully supports both Tensorflow 1.X and 2.X
  - Added two vignettes for demonstrating imputation workflow and
    configuring Python installs/environments
  - Streamlined handling of Python configuration and interface with
    reticulate
  - Added a fast parameter to the complete() function, giving users more
    flexibility on how to handle predicted probabilities for categorical
    and binary variables.
  - Added function add_missingness() to spike-in missingness for
    examples
  - Minor changes to README
  - Minor changes to DESCRIPTION including title and description fields
  - Replaced all instances of cat() with message() for better logging
  - Bug fixes related to GitHub issues

                         Changes in version 0.1                         

  - First release including all core functionality
  - VAE and overimputation diagnostic tests included
  - Easy to use pre/post-processing of data
  - Multiple imputation wrapper of `glm()' for in-built analysis of
    completed data