Skip to content

Latest commit

 

History

History
52 lines (41 loc) · 2.38 KB

NEWS.md

File metadata and controls

52 lines (41 loc) · 2.38 KB

rMIDAS 0.5

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

rMIDAS 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

rMIDAS 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

rMIDAS 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