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Released:
Tools for randomization-based inference in Python
Project description
Description
resample
provides a set of tools for performing randomization-based inference in Python, primarily through the use of bootstrapping methods and Monte Carlo permutation tests. Documentation can be found on Read the Docs.Features
- Bootstrap samples (ordinary or balanced, both with optional stratification) of arrays with arbitrary dimension
- Parametric bootstrap samples (Gaussian, Poisson, gamma, etc.) of one-dimensional arrays
- Bootstrap confidence intervals (percentile or BCa) for any well-defined parameter
- Jackknife estimates of bias and variance
- Randomization-based variants of traditional statistical tests (t-test, ANOVA F-test, K-S test, etc.)
- Tools for working with empirical distributions (cumulative distribution, quantile, and influence functions)
Dependencies
Installation requires numpy and scipy.
Installation
The latest release can be installed from PyPI:
Release historyRelease notifications | RSS feed
1.0.1
1.0.0
0.21
0.2
0.1.33
0.1.32
0.1.31
0.1.3
0.1.2
0.1.1
0.1 yanked
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Filename, size | File type | Python version | Upload date | Hashes |
---|---|---|---|---|
Filename, size resample-1.0.1-py3-none-any.whl (11.8 kB) | File type Wheel | Python version py3 | Upload date | Hashes |
Filename, size resample-1.0.1.tar.gz (10.9 kB) | File type Source | Python version None | Upload date | Hashes |
Hashes for resample-1.0.1-py3-none-any.whl
Resample 1 1 5 3
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BLAKE2-256 | 74497b5171c7c6680f951e9c7038c358973c0061c576e70df9ab8b2172ff2ee8 |
Hashes for resample-1.0.1.tar.gz
Resample 1 1 5 1
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SHA256 | f4f7eec3ba3316e7f573582ef36afc936fb9090b33b14b024981fa26ea2aad60 |
MD5 | dcd96b4a668d74e659d16baebfec97d3 |
BLAKE2-256 | ae32f316b2558a7dd2c6e049d3280dc0276447be202ac6a2b3bf9ae446ce064f |
Released:
Tools for randomization-based inference in Python
Project description
Description
resample
provides a set of tools for performing randomization-based inference in Python, primarily through the use of bootstrapping methods and Monte Carlo permutation tests. Documentation can be found on Read the Docs.Features
- Bootstrap samples (ordinary or balanced, both with optional stratification) of arrays with arbitrary dimension
- Parametric bootstrap samples (Gaussian, Poisson, gamma, etc.) of one-dimensional arrays
- Bootstrap confidence intervals (percentile or BCa) for any well-defined parameter
- Jackknife estimates of bias and variance
- Randomization-based variants of traditional statistical tests (t-test, ANOVA F-test, K-S test, etc.)
- Tools for working with empirical distributions (cumulative distribution, quantile, and influence functions)
Dependencies
![Resample 1 1 5 Resample 1 1 5](https://www.mathworks.com/help/examples/signal/win64/ResampleWithKaiserWindowExample_06.png)
Installation requires numpy and scipy.
Installation
The latest release can be installed from PyPI:
Release historyRelease notifications | RSS feed
1.0.1
1.0.0
Resample 1 1 5 2
0.21
0.2
![Resample Resample](https://media.cheggcdn.com/media/5bb/5bbd8eb3-3ee2-4e66-a872-3507359d1d24/image.png)
0.1.33
0.1.32
Resample 1 1 5
0.1.31
0.1.3
0.1.2
0.1.1
0.1 yanked
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Filename, size | File type | Python version | Upload date | Hashes |
---|---|---|---|---|
Filename, size resample-1.0.1-py3-none-any.whl (11.8 kB) | File type Wheel | Python version py3 | Upload date | Hashes |
Filename, size resample-1.0.1.tar.gz (10.9 kB) | File type Source | Python version None | Upload date | Hashes |
Hashes for resample-1.0.1-py3-none-any.whl
Resample 1 1 5 Scale
Algorithm | Hash digest |
---|---|
SHA256 | c317da2a58e83ef54e603145ef72614c6cc47545cd97555c3fe4cff880204b25 |
MD5 | 01f0afb43a2833a563a2186804d831ae |
BLAKE2-256 | 74497b5171c7c6680f951e9c7038c358973c0061c576e70df9ab8b2172ff2ee8 |
Hashes for resample-1.0.1.tar.gz
Algorithm | Hash digest |
---|---|
SHA256 | f4f7eec3ba3316e7f573582ef36afc936fb9090b33b14b024981fa26ea2aad60 |
MD5 | dcd96b4a668d74e659d16baebfec97d3 |
BLAKE2-256 | ae32f316b2558a7dd2c6e049d3280dc0276447be202ac6a2b3bf9ae446ce064f |