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Model prostora stanja (Kalmanov filtar)×Strukturni model vremenskih nizova (Osnovni strukturni model)×
PodručjeEkonometrijaEkonometrija
ObiteljRegression modelRegression model
Godina nastanka19901990
TvoracHarvey; Durbin & Koopman (state space treatment); Kalman filterAndrew C. Harvey
VrstaState space time series modelState-space (unobserved components) time series model
Temeljni izvorHarvey, A. C. (1990). Forecasting, Structural Time Series Models and the Kalman Filter. Cambridge University Press. DOI ↗Harvey, A. C. (1990). Forecasting, Structural Time Series Models and the Kalman Filter. Cambridge University Press. ISBN: 978-0521405737
Drugi nazivistate space, Kalman filter, unobserved components model, Durum Uzayı Modeli (State Space / Kalman Filter)BSM, basic structural model, unobserved components model, Yapısal Zaman Serisi Modeli (BSM)
Srodne44
SažetakA state space model is a general time series framework that describes a series through unobserved (latent) state variables linked by a measurement equation and a transition equation, with the states estimated in real time by the Kalman filter. Developed in the state space tradition of Harvey (1990) and Durbin & Koopman (2012), it nests ARIMA and exponential smoothing as special cases.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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ScholarGateUsporedite metode: State Space Model · Structural Time Series Model. Preuzeto 2026-06-17 s https://scholargate.app/hr/compare