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Hybrid design of experiments/Evidence
Method evidence record

Hybrid design of experiments

Hybrid design of experiments (hybrid DOE) combines two or more experimental design strategies within a single study to exploit the complementary strengths of each. Common combinations include factorial or fractional-factorial arrays paired with computer simulation runs, space-filling Latin hypercube designs merged with response surface augmentations, or Taguchi orthogonal arrays integrated with response surface methodology. The approach is widely used when a single design type cannot efficiently cover all phases of an engineering investigation — from screening through to optimization.

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Source record

Citations copied verbatim from the method’s source record. No claim-level verification is inferred from them.

Hybrid Design of Experiments
Taxonomic method record · process-pipeline / experimental-design
  • Santner, T. J., Williams, B. J., & Notz, W. I. (2003). The Design and Analysis of Computer Experiments. Springer. · ISBN 978-1441929921
  • Loeppky, J. L., Sacks, J., & Welch, W. J. (2009). Choosing the sample size of a computer experiment: A practical guide. Technometrics, 51(4), 366–376. · DOI 10.1198/TECH.2009.08040
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Related methods

Generated from the method graph and shown as machine-suggested relations — no evidence claim is inferred.

Taxonomic bucketCentral Composite Designmachine-suggested · Relational suggestion, not evidence.Taxonomic bucketDesign of experimentsmachine-suggested · Relational suggestion, not evidence.Used in the same domainResponse Surface Methodologymachine-suggested · Relational suggestion, not evidence.Taxonomic bucketSimulation-assisted design of experimentsmachine-suggested · Relational suggestion, not evidence.

Evidence status

Sources recorded, not reviewed

Bibliographic sources are present. Claim-level evidence review has not been performed.

Sources

2 recorded citations, copied from the method source record.

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