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Diagnostika vlivu (Cookova vzdálenost, DFFITS, pákový efekt)×Kvantilová regrese×
OborStatistikaEkonometrie
RodinaRegression modelRegression model
Rok vzniku19771978
TvůrceR. Dennis Cook (Cook's distance); Belsley, Kuh & Welsch (DFFITS, leverage)Koenker & Bassett
TypRegression diagnosticConditional quantile regression
Původní zdrojCook, R. D. (1977). Detection of Influential Observations in Linear Regression. Technometrics, 19(1), 15-18. DOI ↗Koenker, R. & Bassett, G., Jr. (1978). Regression Quantiles. Econometrica, 46(1), 33-50. DOI ↗
Další názvyCook's distance, DFFITS, leverage, influential observation detectionconditional quantile regression, regression quantiles, Kantil Regresyon
Příbuzné55
ShrnutíInfluence diagnostics are a family of post-fit measures that quantify how much each single observation affects a fitted regression. Cook's distance was introduced by R. Dennis Cook in 1977, with leverage and DFFITS formalised by Belsley, Kuh and Welsch in 1980, to flag the observations that most strongly pull the estimated coefficients.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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ScholarGatePorovnat metody: Influence Diagnostics · Quantile Regression. Získáno 2026-06-15 z https://scholargate.app/cs/compare