方法对比
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| 响应面方法 (RSM)× | 拉丁方设计与拉丁方-希腊方设计× | |
|---|---|---|
| 领域 | 实验设计 | 实验设计 |
| 方法族 | Hypothesis test | Hypothesis test |
| 起源年份≠ | 1951 | 1935 |
| 提出者≠ | George E. P. Box & K. B. Wilson | Ronald A. Fisher |
| 类型≠ | Second-order polynomial response surface model | Parametric blocked ANOVA |
| 开创性文献≠ | Box, G. E. P. & Wilson, K. B. (1951). On the experimental attainment of optimum conditions. Journal of the Royal Statistical Society, Series B, 13(1), 1–45. link ↗ | Montgomery, D. C. (2017). Design and Analysis of Experiments (9th ed.). Wiley. ISBN: 978-1119492443 |
| 别名≠ | RSM, Central Composite Design, Box-Behnken Design, CCD | Latin Square, Greco-Latin Square, Latin Kare ve Greco-Latin Kare Deseni |
| 相关≠ | 7 | 5 |
| 摘要≠ | Response Surface Methodology is a collection of statistical and mathematical techniques for building an empirical second-order polynomial model that relates a continuous response variable to two or more controllable input factors, and then locating the factor settings that optimize that response. The approach was introduced by George E. P. Box and K. B. Wilson in their landmark 1951 paper and has since become a cornerstone of process optimization across engineering, chemistry, food science, and pharmaceutics. | The Latin square design is a blocked experimental design that simultaneously controls two independent nuisance factors — the row block and the column block — so that each treatment appears exactly once in every row and every column of an n×n arrangement. Formalised by Ronald A. Fisher in his 1935 monograph The Design of Experiments, the design dramatically reduces experimental error by absorbing variation from two extraneous sources before the treatment effects are estimated. |
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