方法对比
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| 蒙特卡洛模拟× | 置换 (随机化) 检验× | |
|---|---|---|
| 领域≠ | 决策 | 统计学 |
| 方法族≠ | MCDM | Regression model |
| 起源年份≠ | 1949 | 2005 |
| 提出者≠ | Metropolis, N., Ulam, S. | Good (2005); Edgington & Onghena (2007); resampling tradition |
| 类型≠ | Robustness wrapper — Monte Carlo uncertainty propagation | Nonparametric resampling test |
| 开创性文献≠ | Metropolis, N., Ulam, S. (1949). The Monte Carlo method. Journal of the American Statistical Association DOI ↗ | Good, P. (2005). Permutation, Parametric and Bootstrap Tests of Hypotheses (3rd ed.). Springer. ISBN: 978-0387202792 |
| 别名≠ | — | randomization test, exact permutation test, re-randomization test, Permütasyon Testi |
| 相关≠ | 0 | 5 |
| 摘要≠ | MONTE-CARLO-SIMULATION (Monte Carlo Simulation — Stochastic uncertainty propagation through MCDM model) is a ranking multi-criteria decision-making (MCDM) method introduced by Metropolis, N., Ulam, S. in 1949. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result. | The permutation test is a nonparametric resampling procedure that builds the sampling distribution of a test statistic directly from the data by repeatedly shuffling the group labels. Developed in the resampling tradition and treated systematically by Good (2005) and Edgington & Onghena (2007), it requires no parametric distributional assumption and yields an exact p-value. |
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