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Model SARIMA Parameter Waktu-Bervariasi (TVP-SARIMA)×Model SARIMA×
BidangEkonometrikaEkonometrika
KeluargaRegression modelRegression model
Tahun asal1990s1970 (first edition); 1976 (revised)
PencetusHarvey, A. C.; Durbin, J. & Koopman, S. J. (state-space framework)Box, Jenkins, and Reinsel
TipeTime-varying state-space modelSeasonal time series model
Sumber perintisHarvey, A. C. (1990). Forecasting, Structural Time Series Models and the Kalman Filter. Cambridge University Press. ISBN: 9780521321969Box, G. E. P., Jenkins, G. M., & Reinsel, G. C. (1976). Time Series Analysis: Forecasting and Control (revised ed.). Holden-Day. ISBN: 978-0130607744
AliasTVP-SARIMA, time-varying SARIMA, state-space SARIMA, adaptive SARIMASARIMA, seasonal ARIMA, Box-Jenkins seasonal model, ARIMA with seasonal component
Terkait45
RingkasanThe 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.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.
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ScholarGateBandingkan metode: Time-varying parameter SARIMA model · SARIMA model. Diakses 2026-06-17 dari https://scholargate.app/id/compare