Bootstrap confidence interval estimation routines for SciPy
Scikits.bootstrap provides bootstrap confidence interval algorithms for scipy.
At present, it is rather feature-incomplete and in flux. However, the functions that have been written should be relatively stable as far as results.
Much of the code has been written based off the descriptions from Efron and Tibshirani's Introduction to the Bootstrap, and results should match the results obtained from following those explanations. However, the current ABC code is based off of the modified-BSD-licensed R port of the Efron bootstrap code, as I do not believe I currently have a sufficient understanding of the ABC method to write the code independently.
In any case, please contact me (Constantine Evans <firstname.lastname@example.org>) with any questions or suggestions. I'm trying to add documentation, and will be adding tests as well. I'm especially interested, however, in how the API should actually look; please let me know if you think the package should be organized differently.
The package is licensed under the Modified BSD License.
You can download the latest distribution from PyPI here: http://pypi.python.org/pypi/scikits.bootstrap
You can install scikits.bootstrap for yourself from the terminal by running:
pip install --user scikits.bootstrap
If you want to install it for all users on your machine, do:
pip install scikits.bootstrapOn Linux, do sudo pip install scikits.bootstrap.
This package was discovered in PyPI.