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| Regressione Gamma (GLM)× | Regressione quantilica× | |
|---|---|---|
| Campo≠ | Statistica | Econometria |
| Famiglia | Regression model | Regression model |
| Anno di origine≠ | 1989 | 1978 |
| Ideatore≠ | McCullagh & Nelder (GLM framework) | Koenker & Bassett |
| Tipo≠ | Generalized linear model | Conditional quantile regression |
| Fonte seminale≠ | McCullagh, P. & Nelder, J. A. (1989). Generalized Linear Models (2nd ed.). Chapman and Hall. DOI ↗ | Koenker, R. & Bassett, G., Jr. (1978). Regression Quantiles. Econometrica, 46(1), 33-50. DOI ↗ |
| Alias | gamma GLM, gamma generalized linear model, Gamma Regresyonu (GLM) | conditional quantile regression, regression quantiles, Kantil Regresyon |
| Correlati≠ | 4 | 5 |
| Sintesi≠ | Gamma regression is a generalized linear model that uses the gamma distribution to model a positive, right-skewed continuous outcome. Developed within the GLM framework of McCullagh and Nelder (1989), it is an alternative to ordinary linear regression for variables such as health-care costs, durations, and income. | 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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