Bootstrap

Basic bootstrapping approaches for estimation statistics.

Overview

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

Organization

This repository contains the following:

• bootstrap/: a collection of functions for basic bootstrapping estimates
• bootstrap-corr.ipynb: a notebook which steps through available functionality

Requirements

bootstrap is written in Python, and requires Python >= 3.6.

It has the following dependencies.

• numpy
• scipy
• matplotlib

Installation

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 .

References

For some context & information on estimation statistics, see:

• Editorial on estimation statistics in neuroscience:
  • https://www.eneuro.org/content/6/4/ENEURO.0259-19.2019
• Overview & introduction to estimation statistics:
  • https://www.eneuro.org/content/6/4/ENEURO.0205-19.2019

License

This code is freely available for re-use / adaption / re-mixing etc - though with no guarantees of accuracy.