A frequentist approach to construct confidence intervals by sampling with replacement.
The statistical boostrap method was first introduced by
B. Efron, "Bootstrap methods: another look at the jackknife", Annals of Statistics, 1979, link to pdf.
These lecture notes provide a nice entry-level introduction. More references are given in the code.
If you use code or ideas from this repository for your projects or research, please cite it.
@misc{Muratore_bsci,
author = {Fabio Muratore},
title = {bsci - Constructing frequentist confidence intervals using the statistical bootstrap},
year = {2021},
publisher = {GitHub},
journal = {GitHub repository},
howpublished = {\url{https://github.com/famura/bsci}}
}
To install the core part of the package run
pip install bsci
For (local) development install the dependencies with
pip install -e .[dev]
Play around with the model's parameters in the demo.py script
cd examples
python demo.py