ScholarGate
Asistent

Porovnať metódy

Prezrite si vybrané metódy vedľa seba; riadky, ktoré sa líšia, sú zvýraznené.

Model ARIMA (Autoregressive Integrated Moving Average)×Nelineárny ARDL (NARDL) model×
OdborEkonometriaEkonometria
RodinaRegression modelRegression model
Rok vzniku19702014
TvorcaGeorge Box and Gwilym JenkinsShin, Yu & Greenwood-Nimmo
TypTime series forecasting modelNonlinear cointegration model
Pôvodný zdrojBox, 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 ↗
Ďalšie názvyARIMA, Box-Jenkins model, integrated ARMA, ARIMA(p,d,q)NARDL, nonlinear bounds test, asymmetric ARDL, asymmetric cointegration model
Príbuzné65
ZhrnutieThe 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.
ScholarGateDátová sada
  1. v1
  2. 2 Zdroje
  3. PUBLISHED
  1. v1
  2. 2 Zdroje
  3. PUBLISHED

Prejsť na hľadanie Stiahnuť snímky

ScholarGatePorovnať metódy: ARIMA model · Nonlinear ARDL. Získané 2026-06-19 z https://scholargate.app/sk/compare