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        "description": "# resample\n\nDescription\n--------\n\n`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.  See the [example notebook](https://github.com/dsaxton/resample/blob/master/examples/resample.ipynb) for a brief tutorial.\n\nFeatures\n--------\n\n* Bootstrap samples (ordinary or balanced, both with optional stratification and smoothing) of arrays with arbitrary dimension\n* Parametric bootstrap samples (Gaussian, Poisson, gamma, etc.) of one-dimensional arrays\n* Bootstrap confidence intervals (percentile, BCA and Studentized) for any well-defined parameter\n* Jackknife estimates of bias and variance\n* Randomization-based variants of traditional statistical tests (t-test, ANOVA F-test, K-S test, etc.)\n* Tools for working with empirical distributions (empirical cumulative distribution and quantile functions, empirical influence functions, distance metrics for comparing distributions)\n\nDependencies\n------------\n\nInstallation requires [numpy](http://www.numpy.org/) and [scipy](https://www.scipy.org/).\n\nInstallation\n------------\n\nThe latest release can be installed from PyPI:\n\n    pip install resample",
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