Continuous Time Markov Chain for daily panel data and annual transition probabilities
The panelctmc
git repo is available as PyPi package
pip install panelctmc
Check the examples folder for notebooks.
- Check syntax:
flake8 --ignore=F401
- Run Unit Tests:
python -W ignore -m unittest discover
- Remove
.pyc
files:find . -type f -name "*.pyc" | xargs rm
- Remove
__pycache__
folders:find . -type d -name "__pycache__" | xargs rm -rf
- Upload to PyPi with twine:
python setup.py sdist && twine upload -r pypi dist/*
- Notebooks to profile python code are in the profile folder
Please open an issue for support.
Please contribute using Github Flow. Create a branch, add commits, and open a pull request.