方法对比
并排查看您选择的方法；存在差异的行会高亮显示。
| 最优实验设计（D最优、I最优）× | Plackett-Burman 筛选设计× | |
|---|---|---|
| 领域 | 实验设计 | 实验设计 |
| 方法族 | Hypothesis test | Hypothesis test |
| 起源年份≠ | 1972 | 1946 |
| 提出者≠ | V. V. Fedorov | R.L. Plackett & J.P. Burman |
| 类型≠ | Computer-aided optimal design | Two-level orthogonal array |
| 开创性文献≠ | Fedorov, V.V. (1972). Theory of Optimal Experiments. Academic Press. link ↗ | Plackett, R.L. & Burman, J.P. (1946). The Design of Optimum Multifactorial Experiments. Biometrika, 33(4), 305–325. DOI ↗ |
| 别名≠ | D-Optimal Design, I-Optimal Design, Computer-Generated Design, Optimal Deneme Deseni (D-Optimal, I-Optimal) | PB design, PB screening, Plackett-Burman Tarama Deseni |
| 相关≠ | 5 | 4 |
| 摘要≠ | 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. | The Plackett-Burman design is a two-level orthogonal screening design introduced by R.L. Plackett and J.P. Burman in 1946 that allows researchers to estimate the main effect of each factor independently using the smallest possible number of experimental runs. Run counts are always multiples of four, making it exceptionally economical for studies with many candidate factors. |
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