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| Kvantilis regresszió× | Robuszt kovariancia becslés (MCD)× | |
|---|---|---|
| Tudományterület≠ | Ökonometria | Statisztika |
| Módszercsalád | Regression model | Regression model |
| Keletkezés éve≠ | 1978 | 1999 |
| Megalkotó≠ | Koenker & Bassett | Rousseeuw; Rousseeuw & Van Driessen (Fast-MCD) |
| Típus≠ | Conditional quantile regression | Robust multivariate location-scatter estimator |
| Alapmű≠ | Koenker, R. & Bassett, G., Jr. (1978). Regression Quantiles. Econometrica, 46(1), 33-50. DOI ↗ | Rousseeuw, P. J. & Van Driessen, K. (1999). A Fast Algorithm for the Minimum Covariance Determinant Estimator. Technometrics, 41(3), 212-223. DOI ↗ |
| Alternatív nevek≠ | conditional quantile regression, regression quantiles, Kantil Regresyon | minimum covariance determinant, MCD estimator, robust covariance estimation, Robust Kovaryans Tahmini (MCD) |
| Kapcsolódó≠ | 5 | 4 |
| Összefoglaló≠ | Quantile regression models conditional quantiles of an outcome - the median, the 25th or 75th percentile, and so on - rather than the conditional mean that OLS targets. Introduced by Koenker and Bassett in 1978, it reveals how predictors act across the whole distribution, including its tails. | Robust Covariance via the Minimum Covariance Determinant (MCD) estimates a multivariate mean vector and covariance matrix that are not distorted by outliers. It was made practical by the Fast-MCD algorithm of Rousseeuw and Van Driessen (1999), building on Rousseeuw's earlier work on robust estimation. |
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