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Regressão Quantílica Robusta×Regressão Quantílica×
ÁreaEstatísticaEconometria
FamíliaRegression modelRegression model
Ano de origem1993–19971978
Autor originalKoenker & Bassett (1978); robust extensions by Machado (1993) and He (1997)Koenker & Bassett
TipoRobust semiparametric regressionConditional quantile regression
Fonte seminalKoenker, R. (2005). Quantile Regression. Cambridge University Press. ISBN: 978-0521608275Koenker, R. & Bassett, G., Jr. (1978). Regression Quantiles. Econometrica, 46(1), 33-50. DOI ↗
Outros nomesrobust QR, outlier-resistant quantile regression, bounded-influence quantile regression, RQRconditional quantile regression, regression quantiles, Kantil Regresyon
Relacionados65
ResumoRobust Quantile Regression estimates conditional quantiles of a response variable while simultaneously downweighting the influence of outliers. By combining the asymmetric loss function of standard quantile regression with bounded-influence or M-estimation weights, it provides reliable quantile estimates even when data contain extreme observations or heavy-tailed error distributions.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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ScholarGateComparar métodos: Robust Quantile Regression · Quantile Regression. Recuperado em 2026-06-15 de https://scholargate.app/pt/compare