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This is a quarto presentation on outlier analysis and detection. It relies on the methodology described in the "stray" package.

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RobWiederstein/outliers_pres

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outliers_pres

The outliers_pres is a quarto presentation on outlier analysis. The presentation was accompanied with a release of an interactive dashboard illustrating the concepts. The dashboard is available online here.

Contributing

Contributions are what make the open source community such an amazing place to learn, inspire, and create. Any contributions you make are greatly appreciated.

If you have a suggestion that would make this better, please fork the repo and create a pull request. You can also simply open an issue with the tag "enhancement". Don't forget to give the project a star! Thanks again!

  1. Fork the Project
  2. Create your Feature Branch (git checkout -b feature/AmazingFeature)
  3. Commit your Changes (git commit -m 'Add some AmazingFeature')
  4. Push to the Branch (git push origin feature/AmazingFeature)
  5. Open a Pull Request

License

Distributed under the MIT License. See LICENSE.md for more information.

Acknowledgements

  • Professor Talagala whose academic paper and numerous repositories have been extremely helpful and form the basis of this dashboard.

  • Centers for Medicare and Medicaid Services for the publicly available claims data.

Contact

Rob Wiederstein - Linked In

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This is a quarto presentation on outlier analysis and detection. It relies on the methodology described in the "stray" package.

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