OApackage (Orthogonal Array Package)
OApackage (Orthogonal Array Package): A focused toolkit for constructing and evaluating orthogonal and optimal designs. Ranked #84 of 106 in Statistical Analysis Software by our editors (3.0/10); pricing: Free plan; best for design researchers constructing orthogonal arrays.
At a glance
- Editor score3.0 / 10
- PricingFree plan
- Best forDesign researchers constructing orthogonal arrays
- Free planYes
- Paid fromFree
- DeploymentDesktop
- Facts checked23 Sep 2026
Where it wins
- Generates orthogonal arrays, conference designs and D-efficient designs
- Calculates multiple design-efficiency criteria and structural measures
- Includes Python bindings and command-line array utilities
Where it doesn't
- Specializes in experimental-design arrays rather than general-purpose analysis
- Works with .oa text and binary array files, including gzip-compressed files
- Documentation is the listed support channel
Our verdict on OApackage (Orthogonal Array Package)
OApackage is an open-source Python/C++ package for researchers and practitioners working with orthogonal arrays, conference designs and optimal experimental designs. Its scope is experimental design: it can generate and extend orthogonal-array lists, enumerate arrays, reduce them to normal form, and analyse statistical and structural properties. That makes it a fit for people constructing or assessing designs, rather than those seeking a general-purpose package for hypothesis testing or regression procedures.
Its analytical depth is centered on design quality and structure. OApackage constructs model matrices for main effects and interactions, calculates GWLP, F-values and J-characteristics, and reports D-, Ds-, A- and E-efficiency criteria. It also supports projection-estimation and information-capacity sequences. For design generation, it can produce conference and double-conference designs, plus D-efficient designs using coordinate-exchange optimization. These functions make the package relevant when array construction and evaluation are the core task; they do not make it a substitute for broader statistical workflows.
The package is free and open source, with desktop availability for Windows and Linux. Python bindings and command-line tools provide two ways to work with arrays, including utilities to check, join, split and analyse files. The supported array formats are text and binary .oa files, including gzip-compressed files, so the file workflow is specialized. Documentation is the listed support channel. Choose OApackage if orthogonal-array design, efficiency measures and related combinatorial design work are central to your research. If you need general-purpose statistical tests, regression models or a broader data-analysis environment, its focused design remit points toward another tool.
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OApackage (Orthogonal Array Package) pricing
OApackage (Orthogonal Array Package) fact sheet
| Free plan | Yes |
|---|---|
| Paid from | Free |
| Deployment | Desktop |
| Statistical tests | No |
| Regression models | No |
| Scripting support | Yes |
| Bayesian analysis | No |
| Data import formats | .oa text and binary array files; gzip-compressed files supported |
| Deployment | Desktop |
| Platforms | Windows, Linux |
| Support | Docs |
| Built for | Solo, Small business, Mid-market, Enterprise (editorial estimate) |
| Pricing | Free plan |
| Website | oapackage.readthedocs.io |
| Facts checked | 23 Sep 2026 |
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Reviewed by iTechGuides Editors · Editorial team · Updated Oct 2026
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