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Απλή και Διπλή Εκθετική Εξομάλυνση (SES / Holt)×Δομικό Μοντέλο Χρονοσειρών (Βασικό Δομικό Μοντέλο)×
ΠεδίοΟικονομετρίαΟικονομετρία
ΟικογένειαRegression modelRegression model
Έτος προέλευσης19571990
ΔημιουργόςRobert G. Brown (SES); Charles C. Holt (linear trend)Andrew C. Harvey
ΤύποςExponential smoothing forecasting modelState-space (unobserved components) time series model
Θεμελιώδης πηγήBrown, R. G. (1959). Statistical Forecasting for Inventory Control. McGraw-Hill. link ↗Harvey, A. C. (1990). Forecasting, Structural Time Series Models and the Kalman Filter. Cambridge University Press. ISBN: 978-0521405737
Εναλλακτικές ονομασίεςSES, Holt's linear trend method, exponential smoothing forecasting, Basit ve Çift Üstel Düzleştirme (SES / Holt)BSM, basic structural model, unobserved components model, Yapısal Zaman Serisi Modeli (BSM)
Συναφείς34
ΣύνοψηExponential 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.The Structural Time Series Model, in its Basic Structural Model (BSM) form, is Andrew Harvey's state-space approach that decomposes a series into separate stochastic trend, seasonal, cyclical, and irregular components. Developed in Harvey's 1990 treatment, it is prized for interpretability and component decomposition where ARIMA only delivers a black-box fit.
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ScholarGateΣύγκριση μεθόδων: Exponential Smoothing · Structural Time Series Model. Ανακτήθηκε στις 2026-06-17 από https://scholargate.app/el/compare