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Model nelineárních autokorelačních distribuovaných zpoždění (NARDL)×Regrese metodou ordinárních nejmenších čtverců (OLS)×
OborEkonometrieEkonometrie
RodinaRegression modelRegression model
Rok vzniku20142019
TvůrceShin, Yu, and Greenwood-NimmoWooldridge (textbook treatment); classical least squares
TypNonlinear cointegration modelLinear regression
Původní zdrojShin, Y., Yu, B., & Greenwood-Nimmo, M. (2014). Modelling asymmetric cointegration and dynamic multipliers in a nonlinear ARDL framework. In R. C. Sickles & W. C. Horrace (Eds.), Festschrift in Honor of Peter Schmidt: Econometric Methods and Applications (pp. 281-314). Springer. DOI ↗Wooldridge, J. M. (2019). Introductory Econometrics: A Modern Approach (7th ed.). Cengage Learning. ISBN: 978-1337558860
Další názvyNARDL, nonlinear ARDL, asymmetric ARDL, nonlinear bounds testordinary least squares, classical linear regression, linear regression, en küçük kareler regresyonu
Příbuzné45
ShrnutíThe Nonlinear ARDL (NARDL) model extends the linear ARDL bounds-testing framework to allow asymmetric long-run and short-run relationships. By decomposing an explanatory variable into its positive and negative partial sums, it tests whether increases and decreases in a regressor have different effects on the dependent variable — a feature that linear cointegration methods cannot capture.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).
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ScholarGatePorovnat metody: Nonlinear NARDL · OLS Regression. Získáno 2026-06-15 z https://scholargate.app/cs/compare