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ऑटोरेग्रेसिव इंटीग्रेटेड मूविंग एवरेज (ARIMA) मॉडल×ऑटोरेग्रेसिव मॉडल (AR)×मूविंग एवरेज (MA) मॉडल×
क्षेत्रअर्थमितिअर्थमितिअर्थमिति
परिवारRegression modelRegression modelRegression model
उद्भव वर्ष19701970s (popularised 1976)1970
प्रवर्तकGeorge Box and Gwilym JenkinsGeorge E. P. Box and Gwilym M. JenkinsBox and Jenkins
प्रकारTime series forecasting modelTime series modelLinear time series model
मौलिक स्रोतBox, G. E. P., & Jenkins, G. M. (1970). Time Series Analysis: Forecasting and Control. Holden-Day. link ↗Box, G. E. P., & Jenkins, G. M. (1976). Time Series Analysis: Forecasting and Control (revised ed.). Holden-Day. ISBN: 978-0816211043Box, G. E. P., Jenkins, G. M., & Reinsel, G. C. (1976). Time Series Analysis: Forecasting and Control (revised ed.). Holden-Day. ISBN: 978-0130607744
उपनामARIMA, Box-Jenkins model, integrated ARMA, ARIMA(p,d,q)AR model, AR(p) model, autoregression, AR processMA model, MA(q) process, moving-average process, Box-Jenkins MA
संबंधित665
सारांशThe 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.An autoregressive model of order p — AR(p) — expresses the current value of a time series as a linear function of its own p most recent past values plus a white-noise error. It is the building block of the Box-Jenkins family of time-series models and is widely used for forecasting stationary economic and financial series.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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