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ARIMA model (Autoregresivni integrisani model pokretnih proseka)×Nelinearni model ARDL (NARDL)×
OblastEkonometrijaEkonometrija
PorodicaRegression modelRegression model
Godina nastanka19702014
TvoracGeorge Box and Gwilym JenkinsShin, Yu & Greenwood-Nimmo
TipTime series forecasting modelNonlinear cointegration model
Temeljni izvorBox, G. E. P., & Jenkins, G. M. (1970). Time Series Analysis: Forecasting and Control. Holden-Day. link ↗Shin, 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. link ↗
Drugi naziviARIMA, Box-Jenkins model, integrated ARMA, ARIMA(p,d,q)NARDL, nonlinear bounds test, asymmetric ARDL, asymmetric cointegration model
Srodne65
SažetakThe ARIMA(p,d,q) model is the standard workhorse for univariate time series forecasting. It combines autoregressive terms (past values), differencing to induce stationarity, and moving average terms (past shocks) into a unified linear framework. Developed by Box and Jenkins (1970), it remains one of the most widely applied models in econometrics and applied statistics.The Nonlinear ARDL (NARDL) model extends the linear ARDL bounds-testing framework to allow asymmetric long-run and short-run relationships. By decomposing the regressor into cumulative positive and negative partial sums, it tests whether increases and decreases in a variable exert different effects on the outcome — a feature especially relevant in financial and energy economics where positive and negative shocks rarely cancel out symmetrically.
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ScholarGateUporedite metode: ARIMA model · Nonlinear ARDL. Preuzeto 2026-06-18 sa https://scholargate.app/sr/compare