Σύγκριση μεθόδων

	Μοντέλο Robust ARIMA	Μοντέλο ARIMA (Αυτοπαλινδρομικό Ολοκληρωμένο Κινητό Μέσος Όρος)
Πεδίο	Οικονομετρία	Οικονομετρία
Οικογένεια	Regression model	Regression model
Έτος προέλευσης	1986–1993	1970
Δημιουργός	Tsay (1986); Chen & Liu (1993)	George Box and Gwilym Jenkins
Τύπος	Robust time series model	Time series forecasting model
Θεμελιώδης πηγή	Tsay, R. S. (1986). Time series model specification in the presence of outliers. Journal of the American Statistical Association, 81(393), 132–141.	Box, G. E. P., & Jenkins, G. M. (1970). Time Series Analysis: Forecasting and Control. Holden-Day.
Εναλλακτικές ονομασίες	robust ARIMA, outlier-resistant ARIMA, robust time series estimation, ARIMA with outlier detection	ARIMA, Box-Jenkins model, integrated ARMA, ARIMA(p,d,q)
Συναφείς	4	6
Σύνοψη	Robust ARIMA extends the classical ARIMA framework to detect and correct the influence of outliers and structural breaks during estimation. By jointly identifying anomalous observations and re-estimating model parameters, it produces coefficient estimates and forecasts that are far less distorted by isolated shocks or data errors than standard ARIMA.	The 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.