Vertaile menetelmiä
Tarkastele valitsemiasi menetelmiä rinnakkain; eroavat rivit korostetaan.
| Bootstrap-estimaatti× | Vankka korrelaatio (Spearman, Kendall ja Biweight)× | |
|---|---|---|
| Tieteenala | Tilastotiede | Tilastotiede |
| Menetelmäperhe | Regression model | Regression model |
| Syntyvuosi≠ | 1979 | 2012 |
| Kehittäjä≠ | Bradley Efron | Spearman rank, Kendall tau; biweight from Wilcox / Shevlyakov & Oja robust statistics tradition |
| Tyyppi≠ | Resampling-based inference | Robust correlation measures |
| Alkuperäislähde≠ | 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 |
| Rinnakkaisnimet≠ | bootstrap, bootstrap resampling, nonparametric bootstrap, Bootstrap Çıkarımı | Spearman correlation, Kendall tau, biweight midcorrelation, rank correlation |
| Liittyvät | 5 | 5 |
| Tiivistelmä≠ | 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. |
| ScholarGateAineisto ↗ |
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