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Logistička regresija×Kvantilna regresija×
OblastIstraživačka statistikaEkonometrija
PorodicaProcess / pipelineRegression model
Godina nastanka19581978
TvoracDavid Roxbee CoxKoenker & Bassett
TipMethodConditional quantile regression
Temeljni izvorCox, D. R. (1958). The regression analysis of binary sequences. Journal of the Royal Statistical Society, Series B, 20(2), 215–242. DOI ↗Koenker, R. & Bassett, G., Jr. (1978). Regression Quantiles. Econometrica, 46(1), 33-50. DOI ↗
Drugi nazivilogit model, binomial logistic regression, LRconditional quantile regression, regression quantiles, Kantil Regresyon
Srodne35
SažetakLogistic regression is a statistical method for modeling the probability of a binary outcome (disease present/absent, success/failure) as a function of continuous and categorical predictors. Developed by David Roxbee Cox (1958), it solves the problem of predicting categorical outcomes by applying a logistic transformation to constrain predictions to the [0,1] probability interval, enabling accurate risk stratification, diagnostic prediction, and causal inference in epidemiology, medicine, and social science.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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ScholarGateUporedite metode: Logistic Regression · Quantile Regression. Preuzeto 2026-06-18 sa https://scholargate.app/sr/compare