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Regresión Cuantílica×Regresión por Mínimos Cuadrados Ordinarios (MCO)×
CampoEconometríaEconometría
FamiliaRegression modelRegression model
Año de origen19782019
Autor originalKoenker & BassettWooldridge (textbook treatment); classical least squares
TipoConditional quantile regressionLinear regression
Fuente seminalKoenker, R. & Bassett, G., Jr. (1978). Regression Quantiles. Econometrica, 46(1), 33-50. DOI ↗Wooldridge, J. M. (2019). Introductory Econometrics: A Modern Approach (7th ed.). Cengage Learning. ISBN: 978-1337558860
Aliasconditional quantile regression, regression quantiles, Kantil Regresyonordinary least squares, classical linear regression, linear regression, en küçük kareler regresyonu
Relacionados55
ResumenQuantile 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.Ordinary Least Squares is the classical linear regression method that explains a continuous outcome as a linear combination of predictors. It estimates the coefficients by minimising the sum of squared residuals, and under the Gauss-Markov assumptions these estimates are the best linear unbiased estimator (BLUE).
ScholarGateConjunto de datos
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  2. 2 Fuentes
  3. PUBLISHED
  1. v1
  2. 1 Fuentes
  3. PUBLISHED

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ScholarGateComparar métodos: Quantile Regression · OLS Regression. Recuperado el 2026-06-15 de https://scholargate.app/es/compare