विधियों की तुलना करें
चुनी हुई विधियों की आमने-सामने समीक्षा करें; भिन्नता वाली पंक्तियाँ रेखांकित हैं।
| Holt-Winters ट्रिपल एक्सपोनेंशियल स्मूथिंग× | संरचनात्मक समय श्रृंखला मॉडल (मूल संरचनात्मक मॉडल)× | |
|---|---|---|
| क्षेत्र | अर्थमिति | अर्थमिति |
| परिवार | Regression model | Regression model |
| उद्भव वर्ष≠ | 1960 | 1990 |
| प्रवर्तक≠ | Charles C. Holt and Peter R. Winters | Andrew C. Harvey |
| प्रकार≠ | Exponential smoothing forecasting model | State-space (unobserved components) time series model |
| मौलिक स्रोत≠ | Winters, P. R. (1960). Forecasting Sales by Exponentially Weighted Moving Averages. Management Science, 6(3), 324-342. DOI ↗ | Harvey, A. C. (1990). Forecasting, Structural Time Series Models and the Kalman Filter. Cambridge University Press. ISBN: 978-0521405737 |
| उपनाम | triple exponential smoothing, Winters' method, Holt-Winters seasonal method, Holt-Winters Üçlü Üstel Düzleştirme | BSM, basic structural model, unobserved components model, Yapısal Zaman Serisi Modeli (BSM) |
| संबंधित | 4 | 4 |
| सारांश≠ | Holt-Winters triple exponential smoothing is a forecasting model that extends Holt's double smoothing by adding a seasonal component, introduced by Peter Winters in 1960 building on Charles Holt's work. It tracks three evolving quantities — level, trend, and season — and combines them to forecast a continuous time series. | 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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