Сравнение на методи
Прегледайте избраните методи един до друг; редовете с разлики са откроени.
| Регресия с еластична мрежа× | Квантилна регресия× | |
|---|---|---|
| Област≠ | Статистика | Иконометрия |
| Семейство | Regression model | Regression model |
| Година на възникване≠ | 2005 | 1978 |
| Създател≠ | Hui Zou and Trevor Hastie | Koenker & Bassett |
| Тип≠ | Penalized linear regression | Conditional quantile regression |
| Основополагащ източник≠ | Zou, H., & Hastie, T. (2005). Regularization and variable selection via the elastic net. Journal of the Royal Statistical Society: Series B (Statistical Methodology), 67(2), 301-320. DOI ↗ | Koenker, R. & Bassett, G., Jr. (1978). Regression Quantiles. Econometrica, 46(1), 33-50. DOI ↗ |
| Други названия≠ | elastic net, EN regression, L1+L2 regularized regression, combined lasso-ridge regression | conditional quantile regression, regression quantiles, Kantil Regresyon |
| Свързани≠ | 6 | 5 |
| Резюме≠ | Elastic net regression combines the L1 (lasso) and L2 (ridge) penalties into a single regularized regression framework. Controlled by a mixing parameter alpha and a shrinkage strength lambda, it can simultaneously select variables and handle correlated predictors — overcoming key limitations of pure lasso and pure ridge applied alone. | 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. |
| ScholarGateНабор от данни ↗ |
|
|