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|resample|

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Link to full documentation_

.. _Link to full documentation: http://resample.readthedocs.io

.. skip-marker-do-not-remove

Randomisation-based inference in Python based on data resampling and permutation.

Features

• Bootstrap samples (ordinary or balanced with optional stratification)
• Support for parametric (Gaussian, Poisson, gamma, etc.) and extended bootstrapping (also varies sample size)
• Compute bootstrap confidence intervals (percentile or BCa) for any estimator
• Jackknife estimates of bias and variance of any estimator
• Permutation-based variants of traditional statistical tests (USP test of independence and others)
• Tools for working with empirical distributions (CDF, quantile, etc.)
• Depends only on numpy_ and scipy_
• Optional code acceleration with numba_

Example

.. code-block:: python

  # bootstrap uncertainty of arithmetic mean
  from resample.bootstrap import variance
  import numpy as np

  d = [1, 2, 6, 3, 5]

  print(f"bootstrap {variance(np.mean, d) ** 0.5:.2f} exact {(np.var(d) / len(d)) ** 0.5:.2f}")
  # bootstrap 0.82 exact 0.83

.. _numpy: http://www.numpy.org .. _scipy: https://www.scipy.org .. _numba: https://numba.pydata.org

Installation

You can install with pip, but you need a C compiler on the target machine.

.. code-block:: shell

  pip install resample