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SARIMA model s vremenski promjenjivim parametrima (TVP-SARIMA)×ARIMA model (Autoregressive Integrated Moving Average)×
PodručjeEkonometrijaEkonometrija
ObiteljRegression modelRegression model
Godina nastanka1990s1970
TvoracHarvey, A. C.; Durbin, J. & Koopman, S. J. (state-space framework)George Box and Gwilym Jenkins
VrstaTime-varying state-space modelTime series forecasting model
Temeljni izvorHarvey, A. C. (1990). Forecasting, Structural Time Series Models and the Kalman Filter. Cambridge University Press. ISBN: 9780521321969Box, G. E. P., & Jenkins, G. M. (1970). Time Series Analysis: Forecasting and Control. Holden-Day. link ↗
Drugi naziviTVP-SARIMA, time-varying SARIMA, state-space SARIMA, adaptive SARIMAARIMA, Box-Jenkins model, integrated ARMA, ARIMA(p,d,q)
Srodne46
SažetakThe Time-Varying Parameter SARIMA model extends the classical SARIMA framework by allowing autoregressive and moving-average coefficients to evolve over time. Cast as a state-space system and estimated with the Kalman filter, it captures both seasonal patterns and structural change within a single unified model.The 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.
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ScholarGateUsporedite metode: Time-varying parameter SARIMA model · ARIMA model. Preuzeto 2026-06-18 s https://scholargate.app/hr/compare