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Простое и двойное экспоненциальное сглаживание (SES / Холт)×Сезонная модель ARIMA (SARIMA)×
ОбластьЭконометрикаЭконометрика
СемействоRegression modelRegression model
Год появления19572015
Автор методаRobert G. Brown (SES); Charles C. Holt (linear trend)Box & Jenkins (seasonal extension of ARIMA)
ТипExponential smoothing forecasting modelSeasonal time-series model
Основополагающий источникBrown, R. G. (1959). Statistical Forecasting for Inventory Control. McGraw-Hill. link ↗Box, G.E.P., Jenkins, G.M., Reinsel, G.C. & Ljung, G.M. (2015). Time Series Analysis: Forecasting and Control (5th ed.). Wiley. ISBN: 978-1118675021
Другие названияSES, Holt's linear trend method, exponential smoothing forecasting, Basit ve Çift Üstel Düzleştirme (SES / Holt)seasonal ARIMA, Box-Jenkins seasonal model, SARIMA — Mevsimsel ARIMA
Связанные35
СводкаExponential smoothing is a family of basic time-series forecasting models in which each new observation updates a smoothed estimate by a weighting parameter. Simple exponential smoothing (SES), introduced by Robert G. Brown in 1959, forecasts series with a stable level, while Holt's double exponential smoothing, introduced by Charles C. Holt in 1957, adds a trend term using the parameters alpha and beta.SARIMA is a seasonal extension of the Box-Jenkins ARIMA model that adds seasonal differencing and seasonal autoregressive and moving-average terms. Developed within the Box, Jenkins, Reinsel and Ljung framework (5th edition, 2015), it forecasts series whose pattern repeats on a yearly, monthly, or weekly period.
ScholarGateНабор данных
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  2. 2 Источники
  3. PUBLISHED
  1. v1
  2. 2 Источники
  3. PUBLISHED

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ScholarGateСравнение методов: Exponential Smoothing · SARIMA. Получено 2026-06-18 из https://scholargate.app/ru/compare