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| Estimació per la desviació absoluta mediana (MAD)× | Regressió quantílica× | |
|---|---|---|
| Camp≠ | Estadística | Econometria |
| Família | Regression model | Regression model |
| Any d'origen≠ | 1974 | 1978 |
| Autor original≠ | Hampel (influence-curve treatment); classical robust statistics | Koenker & Bassett |
| Tipus≠ | Robust scale estimator | Conditional quantile regression |
| Font seminal≠ | Hampel, F. R. (1974). The Influence Curve and Its Role in Robust Estimation. Journal of the American Statistical Association, 69(346), 383-393. DOI ↗ | Koenker, R. & Bassett, G., Jr. (1978). Regression Quantiles. Econometrica, 46(1), 33-50. DOI ↗ |
| Àlies≠ | median absolute deviation, MAD scale estimator, robust scale estimation, Medyan Mutlak Sapma (MAD) Tahmini | conditional quantile regression, regression quantiles, Kantil Regresyon |
| Relacionats | 5 | 5 |
| Resum≠ | Median Absolute Deviation estimation is a robust measure of statistical dispersion that replaces the standard deviation when outliers are present. Rooted in the influence-curve framework formalised by Hampel (1974), it summarises the spread of a continuous variable using medians instead of means, so a single extreme value cannot distort the result. | 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. |
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