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funcsim

Lightweight, functional stochastic simulation

Documentation: https://funcsim.readthedocs.io/

Features:

  • static (cross-sectional) and recursive-dynamic simulations from a single user-written function
  • pseudo-random numbers with an explicit seed (so that results are reproducible and comparable across runs or scenarios)
  • stratified/Latin hypercube sampling
  • painless multi-core simulations
  • fitting and comparison of univariate distributions, kernel density estimates, and goodness-of-fit tests
  • multivariate normal (fitted to data or specified by a mean vector and covariance matrix) and multivariate KDE distributions; Gaussian, Student's t, Clayton, Gumbel, and Frank copulas, fitted to pseudo-observations or specified by their parameters (implemented natively, no additional packages required); information-criterion comparison of copula families; Iman-Conover; covariance shrinkage
  • expected utility, cumulative prospect theory, and regret-theoretical expected utility calculations
  • plotly-based fan charts and diagnostic plots
  • highly flexible, and as simple as possible (but no more)
  • functional paradigm

Requirements:

  • python >= 3.11
  • numpy >= 2.2.0
  • scipy >= 1.16.0
  • pandas >= 2.2.0 (pandas 2.2+ and 3.x are both supported)
  • xarray >= 2025.4.0

For optional functionality, additional packages are needed:

  • plotting: plotly (pip install "funcsim[plotting]"); kaleido for static image export

Additionally, to run the tests and build the docs:

  • pytest
  • sphinx, sphinx-autodoc-typehints (pip install "funcsim[docs]")

installation

pip install funcsim

building html docs

From the top-level funcsim directory...

sphinx-build -W -b html docs/source/ docs/build/

running tests

From the top-level funcsim directory...

python3 -m pytest

Metadata

Release files for funcsim 0.2.9

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