fslaborg / fslaborg/FSharp.Stats

Kolmogorov-Smirnov Distribution

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Difficulty: Advanced FsLab Hackathon 2023 Status: Available
Dominant language
F#
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Merged PRs (30d)
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Description

### Description

>The Kolmogorov-Smirnov (KS) two-sided test statistic Dn is widely used to measure the
goodness-of-fit between the empirical distribution of a set of n observations and a given
continuous probability distribution.
Simard & L’Ecuyer (2011) [1]

The Kolmogorov-Smirnov distribution is still missing within the FSharp.Stats probability distributions. This issue requires much domain knowledge since various approximations with different precisions were published over the years. Comparison to other packages is mandatory.
Of course you can start developing in notebooks/scripts and afterwards we try to incorporate into the library.

### References

- [1] Simard, R., & L’Ecuyer, P. (2011). Computing the Two-Sided Kolmogorov-Smirnov Distribution. Journal of Statistical Software, 39(11), 1–18. https://doi.org/10.18637/jss.v039.i11 @ https://www.jstatsoft.org/article/view/v039i11
- [2] https://luk.staff.ugm.ac.id/jurnal/freepdf/IJAS_3-4_2009_07_Facchinetti.pdf
- [3] https://github.com/fslaborg/FSharp.Stats/pull/177

Hints (click to expand if you need additional pointers)

- To be able to contribute to this library you'll need
- an GitHub account
- an IDE like Visual Studio Community or Visual Studio Code
- [dotnet 6 sdk](https://dotnet.microsoft.com/en-us/download)
- to build the binaries yourself follow the [instructions](https://fslab.org/FSharp.Stats/#Installation)
- while working on the [FSharp.Stats documentation](https://fslab.org/FSharp.Stats/) (any file within https://github.com/fslaborg/FSharp.Stats/tree/developer/docs) you can navigate to the project folder with a prompt of your choice and use the command `./build watchdocs`
- unit tests can be executed via `./build runtests`

Contributor guide

Open the contributing guide

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