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मजबूत ARMA मॉडल×ARMA मॉडल (ऑटोरिग्रेसिव मूविंग एवरेज)×
क्षेत्रअर्थमितिअर्थमिति
परिवारRegression modelRegression model
उद्भव वर्ष19861970
प्रवर्तकMartin & Yohai (1986); broader robust time series literatureGeorge E. P. Box and Gwilym M. Jenkins
प्रकारRobust time series modelTime series model
मौलिक स्रोतFranses, P. H., & Ghijsels, H. (1999). Additive outliers, GARCH and forecasting volatility. International Journal of Forecasting, 15(1), 1-9. link ↗Box, G. E. P., & Jenkins, G. M. (1970). Time Series Analysis: Forecasting and Control. Holden-Day. link ↗
उपनामrobust ARMA, outlier-robust ARMA, M-estimator ARMA, resistant ARMA estimationARMA, Box-Jenkins model, autoregressive moving average, AR(p)MA(q)
संबंधित55
सारांशThe Robust ARMA model extends the classical Autoregressive Moving Average framework by replacing the sensitive least-squares loss with outlier-resistant estimation methods — typically M-estimators or median-based approaches. This protects coefficient estimates and forecasts from being distorted by additive outliers, level shifts, or innovational outliers that are common in economic and financial time series.The ARMA(p,q) model describes a stationary time series as a combination of two components: an autoregressive part that regresses the current value on its own past p values, and a moving average part that accounts for past q error terms. It is the foundational framework of the Box-Jenkins methodology for univariate time series modelling and short-run forecasting.
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  1. v1
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  3. PUBLISHED

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