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ARIMA model (Autoregresivni integrisani model pokretnih proseka)×Model pokretnog proseka (MA)×
OblastEkonometrijaEkonometrija
PorodicaRegression modelRegression model
Godina nastanka19701970
TvoracGeorge Box and Gwilym JenkinsBox and Jenkins
TipTime series forecasting modelLinear time series model
Temeljni izvorBox, G. E. P., & Jenkins, G. M. (1970). Time Series Analysis: Forecasting and Control. Holden-Day. link ↗Box, G. E. P., Jenkins, G. M., & Reinsel, G. C. (1976). Time Series Analysis: Forecasting and Control (revised ed.). Holden-Day. ISBN: 978-0130607744
Drugi naziviARIMA, Box-Jenkins model, integrated ARMA, ARIMA(p,d,q)MA model, MA(q) process, moving-average process, Box-Jenkins MA
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 Moving Average model of order q — written MA(q) — expresses the current value of a time series as a linear combination of the current and past random shocks (innovations). Unlike the AR model which uses lagged values of the series itself, the MA model uses lagged error terms, making it well-suited for capturing short-lived disturbances that dissipate over q periods.
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ScholarGateUporedite metode: ARIMA model · Moving Average Model. Preuzeto 2026-06-15 sa https://scholargate.app/sr/compare