DOE¶
This page lists the available algorithms for sampling an input space, a.k.a. design of experiments (DOE). The other feature catalogs are listed on this page.
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This samples are provided either as a file in text or csv format or as a sequence of sequences of numbers.
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Diagonal design of experiments
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The DOE used by the Morris sensitivity analysis.
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The DOE used by a One-factor-at-a-Time sensitivity analysis.
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Axial design
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Composite design
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Factorial design
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Faure sequence
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Full factorial design
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Halton sequence
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Haselgrove sequence
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Latin Hypercube Sampling
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Centered Latin Hypercube Sampling
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Monte Carlo sequence
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Optimal Latin Hypercube Sampling
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Random sampling
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Reverse Halton
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Sobol sequence
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DOE for Sobol indices
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Box-Behnken design
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Central Composite
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2-Level Full-Factorial
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Full-Factorial
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Latin Hypercube Sampling
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Plackett-Burman design
The data of this page were collected on 2026-09-17 from the latest version of each package.