Automatically store/load data in a tidy, efficient way. Includes functions for data visualization and analysis.
Project description
PhD-utils
For people that have to compute and store a large variety of data and/or perform statistical inference.
Keep your files tidy!
Don't spend time creating directories, deciding filenames, saving, loading, etc. Decorators savefig & savedata will do it for you with optimal compression. More info at the tidypath repository.
Estimate confidence intervals
The module phdu.resample allows calls to the resample R package.
- Provides CI and permutation tests.
- CIs can account narrowness bias, skewness and other errors in CI estimation, as indicated in the article
- Alternatively, use
phdu.stats.bootstrapfor numba-accelerated computation (does not callresample).
Bootstrap-based power analysis.
Calculate the power for accepting H0 and estimate the needed sample size.
Function power_analysis in phdu.stats.bootstrap follows Efron-Tshibirani: An introduction to the bootstrap, p. 381-384.
Numba-accelerated permutation tests
Module phdu.stats.tests.permutation.
- Permutation tests for any statistic.
- Includes paired and block cases.
Demo
Please check the example notebook.
Documentation
Install
-
For the R compatible installation first install R:
conda install -c conda-forge r r-essentials r-base -
Install with dependencies:
pip install phdu[dependencies]Where
dependenciescan bebase(recommended),all,r(needed forresampleto work),statsmodels,matplotliborplotly.
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