Hierach
hierarch is a Python package for hierarchical resampling of datasets. It leverages the use of Numba for speeding up key functionalities and is designed with a focus on performance, scalability, and usability.
Key Features
- Hierarchical Resampling: Includes bootstrapping and permutation of datasets.
- Statistical Tools: Helps perform resampling-based hypothesis tests, confidence interval calculations, and power analyses on hierarchical data.
- Automated Tests: Enables automated design-based randomization tests for experiments with varying levels of hierarchy.
Source
The source code for hierarch is available on GitHub.
Installation
Installation is easy and can be done via PyPi or Anaconda.
pip install hierarch
or
conda install -c rkulk111 hierarch
Documentation
Detailed user guide and documentation can be found at readthedocs.
Citation
Hierarch was published in PLoS Computational Biology. If you use Hierarch in your research, please cite:
Kulkarni RU, Wang CL, Bertozzi CR (2022) Analyzing nested experimental designs—A user-friendly resampling method to determine experimental significance. PLoS Comput Biol 18(5): e1010061. https://doi.org/10.1371/journal.pcbi.1010061