方法对比
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| Bootstrap Inference× | 稳健相关（Spearman、Kendall和双权重）× | |
|---|---|---|
| 领域 | 统计学 | 统计学 |
| 方法族 | Regression model | Regression model |
| 起源年份≠ | 1979 | 2012 |
| 提出者≠ | Bradley Efron | Spearman rank, Kendall tau; biweight from Wilcox / Shevlyakov & Oja robust statistics tradition |
| 类型≠ | Resampling-based inference | Robust correlation measures |
| 开创性文献≠ | Efron, B. (1979). Bootstrap Methods: Another Look at the Jackknife. Annals of Statistics, 7(1), 1-26. DOI ↗ | Wilcox, R. R. (2012). Introduction to Robust Estimation and Hypothesis Testing. Academic Press. ISBN: 978-0123869838 |
| 别名≠ | bootstrap, bootstrap resampling, nonparametric bootstrap, Bootstrap Çıkarımı | Spearman correlation, Kendall tau, biweight midcorrelation, rank correlation |
| 相关 | 5 | 5 |
| 摘要≠ | Bootstrap inference, introduced by Bradley Efron in 1979, estimates the sampling distribution of a statistic by repeatedly resampling the observed data with replacement. It requires no distributional assumption and produces reliable confidence intervals even in small samples. | Robust Correlation is a family of association measures that resist outliers, covering Spearman's rank correlation, Kendall's tau, and the biweight midcorrelation. Drawing on the robust-statistics tradition described by Wilcox (2012) and Shevlyakov & Oja (2016), it measures how strongly two variables move together without being distorted by a few extreme points. |
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