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。
| 刀切法估计× | 交叉验证× | |
|---|---|---|
| 领域≠ | 统计学 | 决策 |
| 方法族≠ | Hypothesis test | MCDM |
| 起源年份≠ | 1956 | 1974 |
| 提出者≠ | Maurice Henri Quenouille (bias correction); John W. Tukey (variance estimation and naming) | Stone, M. |
| 类型≠ | Bias and variance estimation | Robustness wrapper — k-fold cross-validation for MCDM stability |
| 开创性文献≠ | Quenouille, M. H. (1956). Notes on Bias in Estimation. Biometrika, 43(3/4), 353–360. DOI ↗ | Stone, M. (1974). Cross-validatory choice and assessment of statistical predictions. Journal of the Royal Statistical Society Series B DOI ↗ |
| 别名≠ | delete-one jackknife, leave-one-out jackknife, Jackknife Yeniden Örnekleme | — |
| 相关≠ | 3 | 0 |
| 摘要≠ | Jackknife estimation is a classical resampling technique that computes the bias and variance of a statistical estimator by systematically leaving out one observation at a time and re-computing the statistic on each reduced sample. Introduced by Maurice Quenouille in 1956 for bias correction and extended by John Tukey in 1958 who coined the name, it is the historical predecessor of the bootstrap and remains analytically tractable for smooth, differentiable estimators. | CROSS-VALIDATION (Cross-Validation — k-fold hold-out validation of MCDM decision consistency) is a ranking multi-criteria decision-making (MCDM) method introduced by Stone, M. in 1974. It turns a decision matrix of alternatives scored on multiple criteria into a structured, reproducible result. |
| ScholarGate数据集 ↗ |
|
|