https://github.com/phrb/experimentaldesign.jl

Design of Experiments in Julia
https://github.com/phrb/experimentaldesign.jl

design-of-experiments experimental-design julia statistical-analysis statistics

Last synced: 18 days ago
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Design of Experiments in Julia

• Host: GitHub
• URL: https://github.com/phrb/experimentaldesign.jl
• Owner: phrb
• License: other
• Created: 2018-03-22T17:28:25.000Z (over 6 years ago)
• Default Branch: master
• Last Pushed: 2022-10-21T22:08:11.000Z (about 2 years ago)
• Last Synced: 2023-08-08T22:27:36.303Z (about 1 year ago)
• Topics: design-of-experiments, experimental-design, julia, statistical-analysis, statistics
• Language: Julia
• Homepage: https://phrb.github.io/ExperimentalDesign.jl/dev/
• Size: 1.34 MB
• Stars: 22
• Watchers: 3
• Forks: 3
• Open Issues: 3
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

        
# ExperimentalDesign

| Build | Docs | Test Coverage |

| --- | --- | --- |

| [![CI](https://github.com/phrb/ExperimentalDesign.jl/actions/workflows/CI.yml/badge.svg?branch=master)](https://github.com/phrb/ExperimentalDesign.jl/actions/workflows/CI.yml) | [![](https://img.shields.io/badge/docs-latest-blue.svg)](https://phrb.github.io/ExperimentalDesign.jl/dev) | [![Coverage Status](https://coveralls.io/repos/github/phrb/ExperimentalDesign.jl/badge.svg?branch=master)](https://coveralls.io/github/phrb/ExperimentalDesign.jl?branch=master) [![codecov.io](http://codecov.io/github/phrb/ExperimentalDesign.jl/coverage.svg?branch=master)](http://codecov.io/github/phrb/ExperimentalDesign.jl?branch=master) |

ExperimentalDesign  provides  tools  for  Design  of  Experiments  in  Julia,

enabling the construction  of designs for screening,  modeling, exploration, and

optimization.

Development  on this  package  is  ongoing, so  expect  things  to change.  Pull

requests are more than welcome!

Check the [documentation](https://phrb.github.io/ExperimentalDesign.jl/dev/)

for the latest features and API, and check the examples directory for

Jupyter Notebooks and code.

Current features are:

- Designs that support categorical and continuous factors

- Integration with [StatsModels](https://github.com/JuliaStats/StatsModels.jl) `@formula`

- Full factorial designs:

  - Explicit: for small designs that fit in memory

  - Iterable: for larger designs, generates experiments on demand

- Two-level fractional factorial designs

- Plackett-Burman designs for screening (check the [example](https://github.com/phrb/ExperimentalDesign.jl/blob/master/examples/Screening%20with%20Plackett-Burman%20Designs.ipynb))

- Box-Behnken and central composite designs for response surface modeling

- Flexible random designs using the [Distributions](https://github.com/JuliaStats/Distributions.jl) package

- Latin Hypercube designs using the [LatinHypercubeSampling.jl](https://github.com/MrUrq/LatinHypercubeSampling.jl) package

- Several variance-optimizing criteria

Intended features include the ones provided by R packages such as

[DoE.base](https://cran.r-project.org/web/packages/DoE.base/index.html),

[FrF2](https://cran.r-project.org/web/packages/FrF2/index.html), and

[AlgDesign](https://cran.r-project.org/web/packages/AlgDesign/index.html).