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Nonparametric Quantile Regression×Estimimi i Dendësisë me Bërthamë dhe Testimi i Shpërndarjes (KDE)×
FushaStatistikëStatistikë
FamiljaRegression modelRegression model
Viti i origjinës19781956
KrijuesiKoenker & BassettRosenblatt (1956); Parzen (1962); textbook treatment by Silverman
LlojiQuantile regression (nonparametric variants)Nonparametric density estimation
Burimi themeluesKoenker, R. & Bassett, G. (1978). Regression Quantiles. Econometrica, 46(1), 33-50. DOI ↗Rosenblatt, M. (1956). Remarks on Some Nonparametric Estimates of a Density Function. Annals of Mathematical Statistics, 27(3), 832-837. DOI ↗
Emërtime të tjeraquantile regression, median regression, distribution-free quantile regression, Kantil Regresyon (Nonparametric Varyantlar)kernel density estimate, KDE, Parzen window estimation, nonparametric density estimation
Të lidhura54
PërmbledhjaQuantile regression, introduced by Koenker and Bassett in 1978, models a chosen conditional quantile (such as the median or the 25th and 75th percentiles) of a continuous outcome rather than its mean. Its nonparametric variants fit these quantile relationships without assuming a distribution for the errors, making them a robust complement to mean-based regression on skewed data.Kernel Density Estimation is a nonparametric method that estimates a continuous probability density by placing a smooth kernel function over each observation, without assuming any parametric distribution. It traces back to Rosenblatt (1956) and the textbook treatment by Silverman (1986), and it also supports distribution-comparison tests built on the estimated densities.
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ScholarGateKrahasoni metodat: Nonparametric Quantile Regression · Kernel Density Estimation. Marrë më 2026-06-15 nga https://scholargate.app/sq/compare