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Regressió per Mínims Quadrats Ordinàris (MQO)×Regressió quantílica×Model de Transició Suau Autorregressiu (STAR)×
CampEconometriaEconometriaEconometria
FamíliaRegression modelRegression modelRegression model
Any d'origen201919781994
Autor originalWooldridge (textbook treatment); classical least squaresKoenker & BassettTeräsvirta (1994); van Dijk, Teräsvirta & Franses (2002)
TipusLinear regressionConditional quantile regressionNonlinear time-series regime-switching model
Font seminalWooldridge, J. M. (2019). Introductory Econometrics: A Modern Approach (7th ed.). Cengage Learning. ISBN: 978-1337558860Koenker, R. & Bassett, G., Jr. (1978). Regression Quantiles. Econometrica, 46(1), 33-50. DOI ↗Teräsvirta, T. (1994). Specification, Estimation, and Evaluation of Smooth Transition Autoregressive Models. Journal of the American Statistical Association, 89(425), 208–218. DOI ↗
Àliesordinary least squares, classical linear regression, linear regression, en küçük kareler regresyonuconditional quantile regression, regression quantiles, Kantil Regresyonsmooth transition autoregressive model, LSTAR, ESTAR, logistic STAR
Relacionats554
ResumOrdinary 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).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.The Smooth Transition Autoregressive (STAR) model is a nonlinear time-series model, developed in Teräsvirta's 1994 framework, that lets the dynamics move smoothly rather than abruptly between two regimes. The logistic variant (LSTAR) captures asymmetric business cycles and the exponential variant (ESTAR) captures purchasing-power-parity deviations.
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ScholarGateCompara mètodes: OLS Regression · Quantile Regression · STAR Model. Recuperat el 2026-06-18 de https://scholargate.app/ca/compare