Сравнение методов

	Модель ARMA (авторегрессионная скользящая средняя)	Модель ARIMA (авторегрессионная интегрированная скользящая средняя)
Область	Эконометрика	Эконометрика
Семейство	Regression model	Regression model
Год появления	1970	1970
Автор метода	George E. P. Box and Gwilym M. Jenkins	George Box and Gwilym Jenkins
Тип	Time series model	Time series forecasting model
Основополагающий источник	Box, G. E. P., & Jenkins, G. M. (1970). Time Series Analysis: Forecasting and Control. Holden-Day.	Box, G. E. P., & Jenkins, G. M. (1970). Time Series Analysis: Forecasting and Control. Holden-Day.
Другие названия	ARMA, Box-Jenkins model, autoregressive moving average, AR(p)MA(q)	ARIMA, Box-Jenkins model, integrated ARMA, ARIMA(p,d,q)
Связанные	5	6
Сводка	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.	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.