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مدل سری زمانی ساختاری (مدل ساختاری پایه)×مدل رژیم-سوئیچینگ مارکوف (MS-AR / MS-VAR)×
حوزهاقتصادسنجیاقتصادسنجی
خانوادهRegression modelRegression model
سال پیدایش19901989
پدیدآورAndrew C. HarveyHamilton (1989); Kim & Nelson (1999)
نوعState-space (unobserved components) time series modelRegime-switching time series model
منبع بنیادینHarvey, A. C. (1990). Forecasting, Structural Time Series Models and the Kalman Filter. Cambridge University Press. ISBN: 978-0521405737Hamilton, J. D. (1989). A New Approach to the Economic Analysis of Nonstationary Time Series and the Business Cycle. Econometrica, 57(2), 357-384. DOI ↗
نام‌های دیگرBSM, basic structural model, unobserved components model, Yapısal Zaman Serisi Modeli (BSM)regime-switching model, Markov-switching autoregression, MS-AR, MS-VAR
مرتبط45
خلاصهThe 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.The Markov regime-switching model lets the parameters of a time series change probabilistically across hidden regimes governed by a Markov chain. Introduced by Hamilton (1989) and developed further by Kim and Nelson (1999), it automatically detects business-cycle phases such as expansions and contractions.
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ScholarGateمقایسهٔ روش‌ها: Structural Time Series Model · Markov-Switching Model. بازیابی‌شده در 2026-06-17 از https://scholargate.app/fa/compare