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Робастная модель ARIMA×Модель SARIMA×
ОбластьЭконометрикаЭконометрика
СемействоRegression modelRegression model
Год появления1986–19931970 (first edition); 1976 (revised)
Автор методаTsay (1986); Chen & Liu (1993)Box, Jenkins, and Reinsel
ТипRobust time series modelSeasonal time series model
Основополагающий источникTsay, R. S. (1986). Time series model specification in the presence of outliers. Journal of the American Statistical Association, 81(393), 132–141. DOI ↗Box, G. E. P., Jenkins, G. M., & Reinsel, G. C. (1976). Time Series Analysis: Forecasting and Control (revised ed.). Holden-Day. ISBN: 978-0130607744
Другие названияrobust ARIMA, outlier-resistant ARIMA, robust time series estimation, ARIMA with outlier detectionSARIMA, seasonal ARIMA, Box-Jenkins seasonal model, ARIMA with seasonal component
Связанные45
СводкаRobust 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.SARIMA extends ARIMA by adding seasonal autoregressive and moving-average operators to capture repeating patterns at fixed intervals — such as monthly, quarterly, or annual cycles. Denoted SARIMA(p,d,q)(P,D,Q)s, it is the standard workhorse for univariate seasonal time series forecasting in econometrics, economics, and official statistics.
ScholarGateНабор данных
  1. v1
  2. 2 Источники
  3. PUBLISHED
  1. v1
  2. 2 Источники
  3. PUBLISHED

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ScholarGateСравнение методов: Robust ARIMA model · SARIMA model. Получено 2026-06-17 из https://scholargate.app/ru/compare