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Generaliserte additive modeller (GAM)×Kvantilregresjon×
FagfeltMaskinlæringØkonometri
FamilieMachine learningRegression model
Opprinnelsesår19861978
OpphavspersonTrevor Hastie & Robert TibshiraniKoenker & Bassett
TypeSemi-parametric additive regression modelConditional quantile regression
Opprinnelig kildeHastie, T., & Tibshirani, R. (1986). Generalized additive models. Statistical Science, 1(3), 297–310. DOI ↗Koenker, R. & Bassett, G., Jr. (1978). Regression Quantiles. Econometrica, 46(1), 33-50. DOI ↗
AliasGAM, additive model, spline-based additive regression, Genelleştirilmiş toplamsal modelconditional quantile regression, regression quantiles, Kantil Regresyon
Relaterte45
SammendragA generalized additive model, introduced by Trevor Hastie and Robert Tibshirani in 1986, extends the generalized linear model by replacing each linear term with a smooth, data-driven function of the predictor. This lets the model capture nonlinear relationships while preserving the additive, term-by-term interpretability of regression: each predictor contributes its own estimated curve, and the curves simply add up (on a link scale) to predict the response.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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ScholarGateSammenlign metoder: Generalized Additive Model · Quantile Regression. Hentet 2026-06-18 fra https://scholargate.app/no/compare