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Optimal Experimental Design/Evidence
Method evidence record

Optimal Experimental Design

Optimal experimental design is a computer-aided approach to constructing experiments that maximises statistical efficiency for a given model and run budget. Formalised by V. V. Fedorov in 1972, it selects experimental points from a candidate set so that the information matrix M = X'X is optimised according to a chosen criterion — most commonly D-optimality (maximising the determinant) or I-optimality (minimising average prediction variance). It is the preferred strategy whenever classical designs such as central composite or Box-Behnken cannot be applied because the experimental region is constrained or factor ranges are irregular.

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Source record

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

Optimal Experimental Design (D-Optimal, I-Optimal)
Taxonomic method record · hypothesis-test / experimental-design
  • Fedorov, V.V. (1972). Theory of Optimal Experiments. Academic Press. · URL
  • Atkinson, A.C., Donev, A.N., & Tobias, R.D. (2007). Optimum Experimental Designs, with SAS. Oxford University Press. · ISBN 978-0199296606
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Related methods

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

Used in the same domainBox-Behnken Designmachine-suggested · Relational suggestion, not evidence.Used in the same domainCentral Composite Designmachine-suggested · Relational suggestion, not evidence.Same method familyFull Factorial Designmachine-suggested · Relational suggestion, not evidence.Same method familyPlackett-Burman Designmachine-suggested · Relational suggestion, not evidence.Same method familyResponse Surface Methodologymachine-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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