- Revamped package structure
- Introduced the high-level function estimate_itr() to provide a easy process to train and evaluate individualized treatment rules.
- Added support for automatic training of many machine learning algorithms including Caret, Superlearner, BART, and Causal Forests.
- Provided plotting tools that automatically creates beautiful plots for evaluation metrics
- Changed output structure to provide more detailed information on evaluation metrics and confidence intervals, integrates with summary() function.
- Added a
NEWS.md
file to track changes to the package.