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Sequential Poisson sampling for Python.

Project description

Sequential Poisson sampling

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Sequential Poisson sampling is a variation of Poisson sampling for drawing probability-proportional-to-size samples with a given number of units, and is commonly used for price-index surveys. This package is a Python implementation of the {sps} R package.

Installation

Install the stable release from PyPI

python -m pip install pysps

or get the development version from github

python -m pip install git+https://github.com/marberts/pysps.git

Usage

The first step to draw a sample is to construct the inclusion probabilties for each unit in the population.

>>> import pysps

>>> pi = pysps.InclusionProb([1, 2, 3, 4], 3)
>>> pi
InclusionProb(array([0.33333333, 0.66666667, 1.        , 1.        ]), 3)

Now these inclusion probabilities can be used to create a sample.

>>> samp = pysps.OrderSample(pi)

>>> samp.units
array([1, 2, 3])

>>> samp.weights
array([1.5, 1.0, 1.0])

Citation

If you use this software, please cite it

@software{pysps,
    author = {Martin, Steve},
    doi = {10.5281/zenodo.15825865},
    license = {MIT},
    title = {{pysps: Sequential Poisson sampling}},
    version = {0.1.1},
    year = {2025}
}

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