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مدل آریما (میانگین متحرک یکپارچه خودرگرسیو)×خودبازگشتی برداری (VAR)×
حوزهاقتصادسنجیاقتصادسنجی
خانوادهRegression modelRegression model
سال پیدایش19701980
پدیدآورGeorge Box and Gwilym JenkinsChristopher A. Sims
نوعTime series forecasting modelMultivariate time-series model
منبع بنیادینBox, G. E. P., & Jenkins, G. M. (1970). Time Series Analysis: Forecasting and Control. Holden-Day. link ↗Sims, C. A. (1980). Macroeconomics and Reality. Econometrica, 48(1), 1–48. DOI ↗
نام‌های دیگرARIMA, Box-Jenkins model, integrated ARMA, ARIMA(p,d,q)VAR, VAR model, vector autoregressive model, multivariate autoregression
مرتبط65
خلاصهThe 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.Vector Autoregression is a multivariate time-series model in which each variable is regressed on its own lags and the lags of all other variables in the system. Originally proposed by Sims (1980) as a data-driven alternative to large structural macroeconomic models, VAR has become the standard workhorse for dynamic analysis in empirical economics and finance.
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ScholarGateمقایسهٔ روش‌ها: ARIMA model · Vector Autoregression. بازیابی‌شده در 2026-06-15 از https://scholargate.app/fa/compare