Порівняння методів
Переглядайте обрані методи поруч; рядки з відмінностями підсвічено.
| Регресія звичайно найменших квадратів (ЗНК)× | Квантильна регресія× | Оцінювання робастної коваріації (MCD)× | |
|---|---|---|---|
| Галузь≠ | Економетрика | Економетрика | Статистика |
| Родина | Regression model | Regression model | Regression model |
| Рік появи≠ | 2019 | 1978 | 1999 |
| Автор методу≠ | Wooldridge (textbook treatment); classical least squares | Koenker & Bassett | Rousseeuw; Rousseeuw & Van Driessen (Fast-MCD) |
| Тип≠ | Linear regression | Conditional quantile regression | Robust multivariate location-scatter estimator |
| Основоположне джерело≠ | Wooldridge, J. M. (2019). Introductory Econometrics: A Modern Approach (7th ed.). Cengage Learning. ISBN: 978-1337558860 | 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 ↗ |
| Інші назви≠ | ordinary least squares, classical linear regression, linear regression, en küçük kareler regresyonu | conditional quantile regression, regression quantiles, Kantil Regresyon | minimum covariance determinant, MCD estimator, robust covariance estimation, Robust Kovaryans Tahmini (MCD) |
| Пов'язані≠ | 5 | 5 | 4 |
| Підсумок≠ | 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). | 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. |
| ScholarGateНабір даних ↗ |
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