So sánh phương pháp

	Mô hình Trung bình Trượt Mạnh mẽ (MA)	Mô hình ARMA (Autoregressive Moving Average)
Lĩnh vực	Kinh tế lượng	Kinh tế lượng
Họ	Regression model	Regression model
Năm ra đời	1979–2009	1970
Người khởi xướng	Denby & Martin (1979); Muler, Pena & Yohai (2009)	George E. P. Box and Gwilym M. Jenkins
Loại	Robust time series model	Time series model
Công trình gốc	Denby, L., & Martin, R. D. (1979). Robust estimation of the first-order autoregressive parameter. Journal of the American Statistical Association, 74(365), 140–146.	Box, G. E. P., & Jenkins, G. M. (1970). Time Series Analysis: Forecasting and Control. Holden-Day.
Tên gọi khác	robust MA, robust moving average, M-estimation MA, bounded-influence MA	ARMA, Box-Jenkins model, autoregressive moving average, AR(p)MA(q)
Liên quan	6	5
Tóm tắt	The Robust MA model applies robust estimation — typically M-estimation or bounded-influence methods — to the Moving Average time series model. By replacing the ordinary least squares loss with a bounded loss function, it produces parameter estimates that are far less sensitive to outliers, additive noise spikes, or heavy-tailed error distributions than the classical Gaussian MA.	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.