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Model nelineárnej autoregresie s distribuovanými oneskoreniami (NARDL)×Regresia metódou najmenších štvorcov (OLS)×
OdborEkonometriaEkonometria
RodinaRegression modelRegression model
Rok vzniku20142019
TvorcaShin, Yu, and Greenwood-NimmoWooldridge (textbook treatment); classical least squares
TypNonlinear cointegration modelLinear regression
Pôvodný 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
Ďalšie názvyNARDL, nonlinear ARDL, asymmetric ARDL, nonlinear bounds testordinary least squares, classical linear regression, linear regression, en küçük kareler regresyonu
Príbuzné45
ZhrnutieThe 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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ScholarGatePorovnať metódy: Nonlinear NARDL · OLS Regression. Získané 2026-06-17 z https://scholargate.app/sk/compare