FSharp.Stats is a multipurpose project for statistical testing, linear algebra, machine learning, fitting and signal processing.
- Linear spline interpolation
- Polynomial interpolation
- Cubic spline interpolation
- Akima subspline interpolation
- Hermite subspline interpolation
- Continuous wavelet transform
- Smoothing filters
- Peak detection
- Singular value decomposition
- PCA
- Clustering
- Surprisal analysis
- Brent minimization
- Bisection
- Nelder Mead
Indepth explanations, tutorials and general information about the project can be found here or at fslab. The documentation and tutorials for this library are automatically generated (using the F# Formatting) from *.fsx and *.md files in the docs folder. If you find a typo, please submit a pull request!
Please refer to the Contribution guidelines.
to build the project, run either build.cmd
or build.sh
depending on your OS.
build targets are defined in the modules of /build/build.fsproj.
Some interesting targets may be:
./build.cmd runtests
will build the project and run tests./build.cmd watchdocs
will build the project, run tests, and build and host a local version of the documentation../build.cmd release
will start the full release pipeline.
The library is available under Apache 2.0. For more information see the License file in the GitHub repository.
FSharp.Stats can be cited using its zenodo record.
Benedikt Venn, Lukas Weil, Kevin Schneider, David Zimmer & Timo Mühlhaus. (2022). fslaborg/FSharp.Stats. Zenodo. https://doi.org/10.5281/zenodo.6337056