مقایسهٔ روش‌ها

	مدل میانگین متحرک با پارامترهای متغیر با زمان	مدل ARMA (میانگین متحرک خودرگرسیو)
حوزه	اقتصادسنجی	اقتصادسنجی
خانواده	Regression model	Regression model
سال پیدایش	1990s	1970
پدیدآور	Harvey, A. C.; Durbin, J. & Koopman, S. J.	George E. P. Box and Gwilym M. Jenkins
نوع	Time-varying state-space model	Time series model
منبع بنیادین	Harvey, A. C. (1990). Forecasting, Structural Time Series Models and the Kalman Filter. Cambridge University Press. ISBN: 9780521321969	Box, G. E. P., & Jenkins, G. M. (1970). Time Series Analysis: Forecasting and Control. Holden-Day.
نام‌های دیگر	TVP-MA model, state-space MA, Kalman filter MA, time-varying MA	ARMA, Box-Jenkins model, autoregressive moving average, AR(p)MA(q)
مرتبط	6	5
خلاصه	The time-varying parameter moving average (TVP-MA) model extends the standard MA model by allowing the moving-average coefficients to change over time. Cast as a state-space system, it is estimated via the Kalman filter and smoother, making it well suited for series where the shock-transmission dynamics evolve across the sample.	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.