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| 강건 상관관계 (스피어만, 켄달, 그리고 바이웨이트)× | 최소제곱법(OLS) 회귀× | |
|---|---|---|
| 분야≠ | 통계학 | 계량경제학 |
| 계열 | Regression model | Regression model |
| 기원 연도≠ | 2012 | 2019 |
| 창시자≠ | Spearman rank, Kendall tau; biweight from Wilcox / Shevlyakov & Oja robust statistics tradition | Wooldridge (textbook treatment); classical least squares |
| 유형≠ | Robust correlation measures | Linear regression |
| 원전≠ | 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 |
| 별칭≠ | Spearman correlation, Kendall tau, biweight midcorrelation, rank correlation | ordinary least squares, classical linear regression, linear regression, en küçük kareler regresyonu |
| 관련 | 5 | 5 |
| 요약≠ | 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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