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| Robustne korrelatsioon (Spearmani, Kendalli ja biweight)× | Tavaline vähimruutude (OLS) regressioon× | |
|---|---|---|
| Valdkond≠ | Statistika | Ökonomeetria |
| Perekond | Regression model | Regression model |
| Tekkeaasta≠ | 2012 | 2019 |
| Looja≠ | Spearman rank, Kendall tau; biweight from Wilcox / Shevlyakov & Oja robust statistics tradition | Wooldridge (textbook treatment); classical least squares |
| Tüüp≠ | Robust correlation measures | Linear regression |
| Algallikas≠ | Wilcox, R. R. (2012). Introduction to Robust Estimation and Hypothesis Testing. Academic Press. ISBN: 978-0123869838 | Wooldridge, J. M. (2019). Introductory Econometrics: A Modern Approach (7th ed.). Cengage Learning. ISBN: 978-1337558860 |
| Rööpnimetused≠ | Spearman correlation, Kendall tau, biweight midcorrelation, rank correlation | ordinary least squares, classical linear regression, linear regression, en küçük kareler regresyonu |
| Seotud | 5 | 5 |
| Kokkuvõte≠ | 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. | Ordinary Least Squares is the classical linear regression method that explains a continuous outcome as a linear combination of predictors. It estimates the coefficients by minimising the sum of squared residuals, and under the Gauss-Markov assumptions these estimates are the best linear unbiased estimator (BLUE). |
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