bootstrap is a mini-module containing basic bootstrapping approaches for estimation statistics.
This repository contains code for doing bootstrapping, primarily for computing confidence intervals, and for correlation measures.
Main functionality:
- using bootstrapping to estimate confidence intervals for correlation measures
- use bootstrapping to compare differences of measures between groups
- computing confidence intervals and estimated p-values of difference measures
This repository contains the following:
bootstrap/: a collection of functions for basic bootstrapping estimatesbootstrap-corr.ipynb: a notebook which steps through available functionality
bootstrap is written in Python, and requires Python >= 3.6.
It has the following dependencies:
The bootstrap module can be installed with pip.
To clone and install this module, you can do:
$ git clone https://github.com/TomDonoghue/bootstrap
$ cd bootstrap
$ pip install .For some context & information on estimation statistics, see:
- This editorial on estimation statistics in neuroscience:
- This overview and introduction to estimation statistics:
This code is freely available for re-use / adaption / re-mixing etc - though with no guarantees of accuracy.
This project welcomes and encourages contributions from the community!
To file bug reports and/or ask questions about this project, please use the Github issue tracker.